p60975123
/
mindspore
forked from mindspore-Ecosystem/mindspore
1
0
Fork 0
Code Issues Pull Requests Projects Releases Wiki Activity

master 03252 sponge ops zoo cu

This commit is contained in:
q00596439 2021-03-25 20:42:18 +08:00
parent a48785cdcc
commit aa7fdf53a7
33 changed files with 441 additions and 198 deletions
Show Stats Download Patch File Download Diff File Expand all files Collapse all files

2
mindspore/ccsrc/backend/kernel_compiler/gpu/cuda_impl/sponge/angle/angle_atom_energy_impl.cu
View File

@ -50,7 +50,7 @@ __global__ void AngleAtomEnergyKernel(int angle_numbers, const UNSIGNED_INT_VECT
void AngleAtomEnergy(int angle_numbers, int atom_numbers, const int *uint_crd_f, const float *scaler_f,
const int *atom_a, const int *atom_b, const int *atom_c, const float *angle_k,
const float *angle_theta0, float *ene, cudaStream_t stream) {
Reset_List<<<ceilf(static_cast<float>(atom_numbers) / 128), 128>>>(atom_numbers, ene, 0.);
Reset_List<<<ceilf(static_cast<float>(atom_numbers) / 128), 128, 0, stream>>>(atom_numbers, ene, 0.);
size_t thread_per_block = 128;
size_t block_per_grid = ceilf(static_cast<float>(angle_numbers) / 128);
UNSIGNED_INT_VECTOR *uint_crd =

2
mindspore/ccsrc/backend/kernel_compiler/gpu/cuda_impl/sponge/angle/angle_force_impl.cu
View File

@ -69,7 +69,7 @@ __global__ void AngleForceKernel(int angle_numbers, const UNSIGNED_INT_VECTOR *u
void AngleForce(int angle_numbers, int atom_numbers, const int *uint_crd_f, const float *scaler_f, const int *atom_a,
const int *atom_b, const int *atom_c, const float *angle_k, const float *angle_theta0, float *frc_f,
cudaStream_t stream) {
Reset_List<<<ceilf(static_cast<float>(3. * atom_numbers) / 128), 128>>>(3 * atom_numbers, frc_f, 0.);
Reset_List<<<ceilf(static_cast<float>(3. * atom_numbers) / 128), 128, 0, stream>>>(3 * atom_numbers, frc_f, 0.);
size_t thread_per_block = 128;
size_t block_per_grid = ceilf(static_cast<float>(angle_numbers) / 128);
UNSIGNED_INT_VECTOR *uint_crd =

2
mindspore/ccsrc/backend/kernel_compiler/gpu/cuda_impl/sponge/angle/angle_force_with_atom_energy_impl.cu
View File

@ -73,7 +73,7 @@ __global__ void AngleForceWithAtomEnergyKernel(int angle_numbers, const UNSIGNED
void AngleForceWithAtomEnergy(int angle_numbers, int atom_numbers, const int *uint_crd_f, const float *scaler_f,
const int *atom_a, const int *atom_b, const int *atom_c, const float *angle_k,
const float *angle_theta0, float *frc_f, float *ene, cudaStream_t stream) {
Reset_List<<<ceilf(static_cast<float>(3. * atom_numbers) / 128), 128>>>(3 * atom_numbers, frc_f, 0.);
Reset_List<<<ceilf(static_cast<float>(3. * atom_numbers) / 128), 128, 0, stream>>>(3 * atom_numbers, frc_f, 0.);
size_t thread_per_block = 128;
size_t block_per_grid = ceilf(static_cast<float>(angle_numbers) / 128);
UNSIGNED_INT_VECTOR *uint_crd =

2
mindspore/ccsrc/backend/kernel_compiler/gpu/cuda_impl/sponge/bond/bond_atom_energy_cuda_gpu_impl.cu
View File

@ -41,7 +41,7 @@ __global__ void BondAtomEnergyCudaKernel(const int bond_numbers, const UNSIGNED_
void BondAtomEnergy(int bond_numbers, int atom_numbers, const int *uint_crd_f, const float *scaler_f, const int *atom_a,
const int *atom_b, const float *bond_k, const float *bond_r0, float *atom_ene,
cudaStream_t stream) {
Reset_List<<<ceilf(static_cast<float>(atom_numbers) / 128), 128>>>(atom_numbers, atom_ene, 0.);
Reset_List<<<ceilf(static_cast<float>(atom_numbers) / 128), 128, 0, stream>>>(atom_numbers, atom_ene, 0.);
size_t thread_per_block = 128;
size_t block_per_grid = ceilf(static_cast<float>(bond_numbers) / 128);
UNSIGNED_INT_VECTOR *uint_crd =

2
mindspore/ccsrc/backend/kernel_compiler/gpu/cuda_impl/sponge/bond/bond_force_cuda_gpu_impl.cu
View File

@ -45,7 +45,7 @@ __global__ void BondForceCudaKernel(int bond_numbers, const UNSIGNED_INT_VECTOR
void BondForce(int bond_numbers, int atom_numbers, const int *uint_crd_f, const float *scaler_f, const int *atom_a,
const int *atom_b, const float *bond_k, const float *bond_r0, float *frc_f, cudaStream_t stream) {
Reset_List<<<ceilf(static_cast<float>(3. * atom_numbers) / 128), 128>>>(3 * atom_numbers, frc_f, 0.);
Reset_List<<<ceilf(static_cast<float>(3. * atom_numbers) / 128), 128, 0, stream>>>(3 * atom_numbers, frc_f, 0.);
size_t thread_per_block = 128;
size_t block_per_grid = ceilf(static_cast<float>(bond_numbers) / 128);
UNSIGNED_INT_VECTOR *uint_crd =

4
mindspore/ccsrc/backend/kernel_compiler/gpu/cuda_impl/sponge/bond/bond_force_with_atom_energy_impl.cu
View File

@ -52,8 +52,8 @@ __global__ void BondForceWithAtomEnergyKernel(int bond_numbers, const UNSIGNED_I
void BondForceWithAtomEnergy(int bond_numbers, int atom_numbers, const int *uint_crd_f, const float *scaler_f,
const int *atom_a, const int *atom_b, const float *bond_k, const float *bond_r0,
float *frc_f, float *atom_e, cudaStream_t stream) {
Reset_List<<<ceilf(static_cast<float>(3. * atom_numbers) / 128), 128>>>(3 * atom_numbers, frc_f, 0.);
Reset_List<<<ceilf(static_cast<float>(atom_numbers) / 128), 128>>>(atom_numbers, atom_e, 0.);
Reset_List<<<ceilf(static_cast<float>(3. * atom_numbers) / 128), 128, 0, stream>>>(3 * atom_numbers, frc_f, 0.);
Reset_List<<<ceilf(static_cast<float>(atom_numbers) / 128), 128, 0, stream>>>(atom_numbers, atom_e, 0.);
size_t thread_per_block = 128;
size_t block_per_grid = ceilf(static_cast<float>(bond_numbers) / 128);
UNSIGNED_INT_VECTOR *uint_crd =

4
mindspore/ccsrc/backend/kernel_compiler/gpu/cuda_impl/sponge/bond/bond_force_with_atom_virial_impl.cu
View File

@ -52,8 +52,8 @@ __global__ void BondForceWithAtomVirialKernel(int bond_numbers, const UNSIGNED_I
void BondForceWithAtomVirial(int bond_numbers, int atom_numbers, const int *uint_crd_f, const float *scaler_f,
const int *atom_a, const int *atom_b, const float *bond_k, const float *bond_r0,
float *frc_f, float *atom_v, cudaStream_t stream) {
Reset_List<<<ceilf(static_cast<float>(3. * atom_numbers) / 128), 128>>>(3 * atom_numbers, frc_f, 0.);
Reset_List<<<ceilf(static_cast<float>(atom_numbers) / 128), 128>>>(atom_numbers, atom_v, 0.);
Reset_List<<<ceilf(static_cast<float>(3. * atom_numbers) / 128), 128, 0, stream>>>(3 * atom_numbers, frc_f, 0.);
Reset_List<<<ceilf(static_cast<float>(atom_numbers) / 128), 128, 0, stream>>>(atom_numbers, atom_v, 0.);
size_t thread_per_block = 128;
size_t block_per_grid = ceilf(static_cast<float>(bond_numbers) / 128);
UNSIGNED_INT_VECTOR *uint_crd =

2
mindspore/ccsrc/backend/kernel_compiler/gpu/cuda_impl/sponge/dihedral/dihedral_atom_energy_impl.cu
View File

@ -67,7 +67,7 @@ void DihedralAtomEnergy(int dihedral_numbers, int atom_numbers, const int *uint_
const int *atom_a, const int *atom_b, const int *atom_c, const int *atom_d, const int *ipn,
const float *pk, const float *gamc, const float *gams, const float *pn, float *ene,
cudaStream_t stream) {
Reset_List<<<ceilf(static_cast<float>(atom_numbers) / 128), 128>>>(atom_numbers, ene, 0.);
Reset_List<<<ceilf(static_cast<float>(atom_numbers) / 128), 128, 0, stream>>>(atom_numbers, ene, 0.);
size_t thread_per_block = 128;
size_t block_per_grid = ceilf(static_cast<float>(dihedral_numbers) / 128);
UNSIGNED_INT_VECTOR *uint_crd =

2
mindspore/ccsrc/backend/kernel_compiler/gpu/cuda_impl/sponge/dihedral/dihedral_force_impl.cu
View File

@ -103,7 +103,7 @@ void DihedralForce(int dihedral_numbers, int atom_numbers, const int *uint_crd_f
const int *atom_a, const int *atom_b, const int *atom_c, const int *atom_d, const int *ipn,
const float *pk, const float *gamc, const float *gams, const float *pn, float *frc_f,
cudaStream_t stream) {
Reset_List<<<ceilf(static_cast<float>(3. * atom_numbers) / 128), 128>>>(3 * atom_numbers, frc_f, 0.);
Reset_List<<<ceilf(static_cast<float>(3. * atom_numbers) / 128), 128, 0, stream>>>(3 * atom_numbers, frc_f, 0.);
size_t thread_per_block = 128;
size_t block_per_grid = ceilf(static_cast<float>(dihedral_numbers) / 128);
UNSIGNED_INT_VECTOR *uint_crd =

2
mindspore/ccsrc/backend/kernel_compiler/gpu/cuda_impl/sponge/dihedral/dihedral_force_with_atom_energy_impl.cu
View File

@ -107,7 +107,7 @@ void DihedralForceWithAtomEnergy(int dihedral_numbers, int atom_numbers, const i
const int *atom_a, const int *atom_b, const int *atom_c, const int *atom_d,
const int *ipn, const float *pk, const float *gamc, const float *gams, const float *pn,
float *frc_f, float *ene, cudaStream_t stream) {
Reset_List<<<ceilf(static_cast<float>(3. * atom_numbers) / 128), 128>>>(3 * atom_numbers, frc_f, 0.);
Reset_List<<<ceilf(static_cast<float>(3. * atom_numbers) / 128), 128, 0, stream>>>(3 * atom_numbers, frc_f, 0.);
size_t thread_per_block = 128;
size_t block_per_grid = ceilf(static_cast<float>(dihedral_numbers) / 128);
UNSIGNED_INT_VECTOR *uint_crd =

2
mindspore/ccsrc/backend/kernel_compiler/gpu/cuda_impl/sponge/lj/lj_force_impl.cu
View File

@ -92,7 +92,7 @@ void LJForce(const int atom_numbers, const float cutoff_square, const int *uint_
const float *charge, const float *scaler_f, float *uint_crd_with_LJ, int *nl_atom_numbers,
int *nl_atom_serial, int *nl, const float *d_LJ_A, const float *d_LJ_B, float *frc_f,
cudaStream_t stream) {
Reset_List<<<ceilf(static_cast<float>(3. * atom_numbers) / 128), 128>>>(3 * atom_numbers, frc_f, 0.);
Reset_List<<<ceilf(static_cast<float>(3. * atom_numbers) / 128), 128, 0, stream>>>(3 * atom_numbers, frc_f, 0.);
VECTOR *frc = reinterpret_cast<VECTOR *>(frc_f);
VECTOR *scaler = const_cast<VECTOR *>(reinterpret_cast<const VECTOR *>(scaler_f));
int max_neighbor_numbers = 800;

2
mindspore/ccsrc/backend/kernel_compiler/gpu/cuda_impl/sponge/lj/lj_force_with_pme_direct_force_impl.cu
View File

@ -106,7 +106,7 @@ void LJForceWithPMEDirectForce(const int atom_numbers, const float cutoff, const
const int *LJtype, const float *charge, const float *scaler_f, float *uint_crd_with_LJ,
int *nl_atom_numbers, int *nl_atom_serial, int *nl, const float *d_LJ_A,
const float *d_LJ_B, float *frc_f, cudaStream_t stream) {
Reset_List<<<ceilf(static_cast<float>(3. * atom_numbers) / 128), 128>>>(3 * atom_numbers, frc_f, 0.);
Reset_List<<<ceilf(static_cast<float>(3. * atom_numbers) / 128), 128, 0, stream>>>(3 * atom_numbers, frc_f, 0.);
VECTOR *frc = reinterpret_cast<VECTOR *>(frc_f);
VECTOR *scaler = const_cast<VECTOR *>(reinterpret_cast<const VECTOR *>(scaler_f));
int max_neighbor_numbers = 800;

2
mindspore/ccsrc/backend/kernel_compiler/gpu/cuda_impl/sponge/nb14/dihedral_14_cf_atom_energy_impl.cu
View File

@ -66,7 +66,7 @@ void Dihedral14CFAtomEnergy(const int dihedral_14_numbers, const int atom_number
atom_numbers, uint_crd, uint_crd_with_LJ, LJtype, charge);
VECTOR *boxlength = const_cast<VECTOR *>(reinterpret_cast<const VECTOR *>(boxlength_f));
Reset_List<<<ceilf(static_cast<float>(3. * atom_numbers) / 128), 128>>>(atom_numbers, ene, 0.);
Reset_List<<<ceilf(static_cast<float>(3. * atom_numbers) / 128), 128, 0, stream>>>(atom_numbers, ene, 0.);
Dihedral14CFAtomEnergyKernel<<<block_per_grid, thread_per_block, 0, stream>>>(
dihedral_14_numbers, uint_crd_with_LJ, boxlength, a_14, b_14, cf_scale_factor, ene);

15
mindspore/ccsrc/backend/kernel_compiler/gpu/cuda_impl/sponge/nb14/dihedral_14_cf_energy_impl.cu
View File

@ -52,21 +52,20 @@ __global__ void Dihedral14CFEnergyKernel(const int dihedral_14_numbers, const UI
}
void Dihedral14CFEnergy(const int dihedral_14_numbers, const int atom_numbers, const int *uint_crd_f, const int *LJtype,
const float *charge, const float *boxlength_f, const int *a_14, const int *b_14,
const float *cf_scale_factor, float *ene, cudaStream_t stream) {
const float *charge, float *uint_crd_with_LJ_f, const float *boxlength_f, const int *a_14,
const int *b_14, const float *cf_scale_factor, float *ene, cudaStream_t stream) {
size_t thread_per_block = 128;
size_t block_per_grid = ceilf(static_cast<float>(atom_numbers) / 128);
UINT_VECTOR_LJ_TYPE *uint_crd_with_LJ = NULL;
Cuda_Malloc_Safely(reinterpret_cast<void **>(&uint_crd_with_LJ), sizeof(UINT_VECTOR_LJ_TYPE) * atom_numbers);
UNSIGNED_INT_VECTOR *uint_crd =
const_cast<UNSIGNED_INT_VECTOR *>(reinterpret_cast<const UNSIGNED_INT_VECTOR *>(uint_crd_f));
UINT_VECTOR_LJ_TYPE *uint_crd_with_LJ = reinterpret_cast<UINT_VECTOR_LJ_TYPE *>(uint_crd_with_LJ_f);
Copy_Crd_To_New_Crd_Start<<<ceilf(static_cast<float>(atom_numbers) / 32), 32, 0, stream>>>(
atom_numbers, uint_crd, uint_crd_with_LJ, LJtype, charge);
VECTOR *boxlength = const_cast<VECTOR *>(reinterpret_cast<const VECTOR *>(boxlength_f));
Reset_List<<<ceilf(static_cast<float>(3. * atom_numbers) / 128), 128>>>(atom_numbers, ene, 0.);
Reset_List<<<ceilf(static_cast<float>(3. * atom_numbers) / 128), 128, 0, stream>>>(atom_numbers, ene, 0.);
Dihedral14CFEnergyKernel<<<block_per_grid, thread_per_block, 0, stream>>>(
dihedral_14_numbers, uint_crd_with_LJ, boxlength, a_14, b_14, cf_scale_factor, ene);
@ -76,5 +75,5 @@ void Dihedral14CFEnergy(const int dihedral_14_numbers, const int atom_numbers, c
}
void Dihedral14CFEnergy(const int dihedral_14_numbers, const int atom_numbers, const int *uint_crd_f, const int *LJtype,
const float *charge, const float *boxlength_f, const int *a_14, const int *b_14,
const float *cf_scale_factor, float *ene, cudaStream_t stream);
const float *charge, float *uint_crd_with_LJ_f, const float *boxlength_f, const int *a_14,
const int *b_14, const float *cf_scale_factor, float *ene, cudaStream_t stream);

4
mindspore/ccsrc/backend/kernel_compiler/gpu/cuda_impl/sponge/nb14/dihedral_14_cf_energy_impl.cuh
View File

@ -20,6 +20,6 @@
#include "runtime/device/gpu/cuda_common.h"
void Dihedral14CFEnergy(const int dihedral_14_numbers, const int atom_numbers, const int *uint_crd_f, const int *LJtype,
const float *charge, const float *boxlength, const int *a_14, const int *b_14,
const float *cf_scale_factor, float *ene, cudaStream_t stream);
const float *charge, float *uint_crd_with_LJ_f, const float *boxlength_f, const int *a_14,
const int *b_14, const float *cf_scale_factor, float *ene, cudaStream_t stream);
#endif // MINDSPORE_CCSRC_KERNEL_GPU_CUDA_IMPL_SPONGE_NB14_DIHEDRAL_14_CF_ENERGY_IMPL_H

2
mindspore/ccsrc/backend/kernel_compiler/gpu/cuda_impl/sponge/nb14/dihedral_14_lj_atom_energy_impl.cu
View File

@ -87,7 +87,7 @@ void Dihedral14LJAtomEnergy(const int dihedral_14_numbers, const int atom_number
atom_numbers, uint_crd, uint_crd_with_LJ, LJtype, charge);
VECTOR *boxlength = const_cast<VECTOR *>(reinterpret_cast<const VECTOR *>(boxlength_f));
Reset_List<<<ceilf(static_cast<float>(3. * atom_numbers) / 128), 128>>>(atom_numbers, ene, 0.);
Reset_List<<<ceilf(static_cast<float>(3. * atom_numbers) / 128), 128, 0, stream>>>(atom_numbers, ene, 0.);
Dihedral14LJAtomEnergyKernel<<<block_per_grid, thread_per_block, 0, stream>>>(
dihedral_14_numbers, uint_crd_with_LJ, boxlength, a_14, b_14, lj_scale_factor, LJ_type_A, LJ_type_B, ene);

28
mindspore/ccsrc/backend/kernel_compiler/gpu/cuda_impl/sponge/nb14/dihedral_14_lj_cf_force_with_atom_energy_impl.cu
View File

@ -105,22 +105,23 @@ __global__ void Dihedral14LJCFForceWithAtomEnergyKernel(const int dihedral_14_nu
}
void Dihedral14LJCFForceWithAtomEnergy(const int dihedral_14_numbers, const int atom_numbers, const int *uint_crd_f,
const int *LJtype, const float *charge, const float *boxlength_f,
const int *a_14, const int *b_14, const float *lj_scale_factor,
const float *cf_scale_factor, const float *LJ_type_A, const float *LJ_type_B,
float *frc_f, float *atom_energy, cudaStream_t stream) {
const int *LJtype, const float *charge, float *uint_crd_with_LJ_f,
const float *boxlength_f, const int *a_14, const int *b_14,
const float *lj_scale_factor, const float *cf_scale_factor,
const float *LJ_type_A, const float *LJ_type_B, float *frc_f, float *atom_energy,
cudaStream_t stream) {
size_t thread_per_block = 128;
size_t block_per_grid = ceilf(static_cast<float>(atom_numbers) / 128);
UINT_VECTOR_LJ_TYPE *uint_crd_with_LJ = NULL;
Cuda_Malloc_Safely(reinterpret_cast<void **>(&uint_crd_with_LJ), sizeof(UINT_VECTOR_LJ_TYPE) * atom_numbers);
UNSIGNED_INT_VECTOR *uint_crd =
const_cast<UNSIGNED_INT_VECTOR *>(reinterpret_cast<const UNSIGNED_INT_VECTOR *>(uint_crd_f));
UINT_VECTOR_LJ_TYPE *uint_crd_with_LJ = reinterpret_cast<UINT_VECTOR_LJ_TYPE *>(uint_crd_with_LJ_f);
Copy_Crd_To_New_Crd_Start<<<ceilf(static_cast<float>(atom_numbers) / 32), 32, 0, stream>>>(
atom_numbers, uint_crd, uint_crd_with_LJ, LJtype, charge);
Reset_List<<<ceilf(static_cast<float>(3. * atom_numbers) / 128), 128>>>(3 * atom_numbers, frc_f, 0.);
Reset_List<<<ceilf(static_cast<float>(3. * atom_numbers) / 128), 128>>>(atom_numbers, atom_energy, 0.);
Reset_List<<<ceilf(static_cast<float>(3. * atom_numbers) / 128), 128, 0, stream>>>(3 * atom_numbers, frc_f, 0.);
Reset_List<<<ceilf(static_cast<float>(3. * atom_numbers) / 128), 128, 0, stream>>>(atom_numbers, atom_energy, 0.);
VECTOR *boxlength = const_cast<VECTOR *>(reinterpret_cast<const VECTOR *>(boxlength_f));
VECTOR *frc = const_cast<VECTOR *>(reinterpret_cast<const VECTOR *>(frc_f));
@ -133,8 +134,9 @@ void Dihedral14LJCFForceWithAtomEnergy(const int dihedral_14_numbers, const int
return;
}
void Dihedral14LJForceWithDirectCF(const int dihedral_14_numbers, const int atom_numbers, const int *uint_crd_f,
const int *LJtype, const float *charge, const float *boxlength_f, const int *a_14,
const int *b_14, const float *lj_scale_factor, const float *cf_scale_factor,
const float *LJ_type_A, const float *LJ_type_B, float *frc, float *atom_energy,
void Dihedral14LJCFForceWithAtomEnergy(const int dihedral_14_numbers, const int atom_numbers, const int *uint_crd_f,
const int *LJtype, const float *charge, float *uint_crd_with_LJ_f,
const float *boxlength_f, const int *a_14, const int *b_14,
const float *lj_scale_factor, const float *cf_scale_factor,
const float *LJ_type_A, const float *LJ_type_B, float *frc_f, float *atom_energy,
cudaStream_t stream);

9
mindspore/ccsrc/backend/kernel_compiler/gpu/cuda_impl/sponge/nb14/dihedral_14_lj_cf_force_with_atom_energy_impl.cuh
View File

@ -20,8 +20,9 @@
#include "runtime/device/gpu/cuda_common.h"
void Dihedral14LJCFForceWithAtomEnergy(const int dihedral_14_numbers, const int atom_numbers, const int *uint_crd_f,
const int *LJtype, const float *charge, const float *boxlength_f,
const int *a_14, const int *b_14, const float *lj_scale_factor,
const float *cf_scale_factor, const float *LJ_type_A, const float *LJ_type_B,
float *frc, float *atom_energy, cudaStream_t stream);
const int *LJtype, const float *charge, float *uint_crd_with_LJ_f,
const float *boxlength_f, const int *a_14, const int *b_14,
const float *lj_scale_factor, const float *cf_scale_factor,
const float *LJ_type_A, const float *LJ_type_B, float *frc_f, float *atom_energy,
cudaStream_t stream);
#endif // MINDSPORE_CCSRC_KERNEL_GPU_CUDA_IMPL_SPONGE_NB14_DIHEDRAL_14_LJ_CF_FORCE_WITH_ATOM_ENERGY_IMPL_H

19
mindspore/ccsrc/backend/kernel_compiler/gpu/cuda_impl/sponge/nb14/dihedral_14_lj_energy_impl.cu
View File

@ -72,20 +72,19 @@ __global__ void Dihedral14LJEnergyKernel(const int dihedral_14_numbers, const UI
}
void Dihedral14LJEnergy(const int dihedral_14_numbers, const int atom_numbers, const int *uint_crd_f, const int *LJtype,
const float *charge, const float *boxlength_f, const int *a_14, const int *b_14,
const float *lj_scale_factor, const float *LJ_type_A, const float *LJ_type_B, float *ene,
cudaStream_t stream) {
const float *charge, float *uint_crd_with_LJ_f, const float *boxlength_f, const int *a_14,
const int *b_14, const float *lj_scale_factor, const float *LJ_type_A, const float *LJ_type_B,
float *ene, cudaStream_t stream) {
size_t thread_per_block = 128;
size_t block_per_grid = ceilf(static_cast<float>(atom_numbers) / 128);
UINT_VECTOR_LJ_TYPE *uint_crd_with_LJ = NULL;
Cuda_Malloc_Safely(reinterpret_cast<void **>(&uint_crd_with_LJ), sizeof(UINT_VECTOR_LJ_TYPE) * atom_numbers);
UNSIGNED_INT_VECTOR *uint_crd =
const_cast<UNSIGNED_INT_VECTOR *>(reinterpret_cast<const UNSIGNED_INT_VECTOR *>(uint_crd_f));
UINT_VECTOR_LJ_TYPE *uint_crd_with_LJ = reinterpret_cast<UINT_VECTOR_LJ_TYPE *>(uint_crd_with_LJ_f);
Copy_Crd_To_New_Crd_Start<<<ceilf(static_cast<float>(atom_numbers) / 32), 32, 0, stream>>>(
atom_numbers, uint_crd, uint_crd_with_LJ, LJtype, charge);
Reset_List<<<ceilf(static_cast<float>(3. * atom_numbers) / 128), 128>>>(dihedral_14_numbers, ene, 0.);
Reset_List<<<ceilf(static_cast<float>(3. * atom_numbers) / 128), 128, 0, stream>>>(dihedral_14_numbers, ene, 0.);
VECTOR *boxlength = const_cast<VECTOR *>(reinterpret_cast<const VECTOR *>(boxlength_f));
Dihedral14LJEnergyKernel<<<block_per_grid, thread_per_block, 0, stream>>>(
@ -97,6 +96,6 @@ void Dihedral14LJEnergy(const int dihedral_14_numbers, const int atom_numbers, c
}
void Dihedral14LJEnergy(const int dihedral_14_numbers, const int atom_numbers, const int *uint_crd_f, const int *LJtype,
const float *charge, const float *boxlength_f, const int *a_14, const int *b_14,
const float *lj_scale_factor, const float *LJ_type_A, const float *LJ_type_B, float *ene,
cudaStream_t stream);
const float *charge, float *uint_crd_with_LJ_f, const float *boxlength_f, const int *a_14,
const int *b_14, const float *lj_scale_factor, const float *LJ_type_A, const float *LJ_type_B,
float *ene, cudaStream_t stream);

6
mindspore/ccsrc/backend/kernel_compiler/gpu/cuda_impl/sponge/nb14/dihedral_14_lj_energy_impl.cuh
View File

@ -20,8 +20,8 @@
#include "runtime/device/gpu/cuda_common.h"
void Dihedral14LJEnergy(const int dihedral_14_numbers, const int atom_numbers, const int *uint_crd_f, const int *LJtype,
const float *charge, const float *boxlength_f, const int *a_14, const int *b_14,
const float *lj_scale_factor, const float *LJ_type_A, const float *LJ_type_B, float *ene,
cudaStream_t stream);
const float *charge, float *uint_crd_with_LJ_f, const float *boxlength_f, const int *a_14,
const int *b_14, const float *lj_scale_factor, const float *LJ_type_A, const float *LJ_type_B,
float *ene, cudaStream_t stream);
#endif // MINDSPORE_CCSRC_KERNEL_GPU_CUDA_IMPL_SPONGE_NB14_DIHEDRAL_14_LJ_ENERGY_IMPL_H

2
mindspore/ccsrc/backend/kernel_compiler/gpu/cuda_impl/sponge/nb14/dihedral_14_lj_force_with_direct_cf_impl.cu
View File

@ -108,7 +108,7 @@ void Dihedral14LJForceWithDirectCF(const int dihedral_14_numbers, const int atom
atom_numbers, uint_crd, uint_crd_with_LJ, LJtype, charge);
cudaStreamSynchronize(stream);
VECTOR *boxlength = const_cast<VECTOR *>(reinterpret_cast<const VECTOR *>(boxlength_f));
Reset_List<<<ceilf(static_cast<float>(3. * atom_numbers) / 128), 128>>>(3 * atom_numbers, frc_f, 0.);
Reset_List<<<ceilf(static_cast<float>(3. * atom_numbers) / 128), 128, 0, stream>>>(3 * atom_numbers, frc_f, 0.);
VECTOR *frc = const_cast<VECTOR *>(reinterpret_cast<const VECTOR *>(frc_f));
Dihedral14LJForceWithDirectCFKernel<<<block_per_grid, thread_per_block, 0, stream>>>(

3
mindspore/ccsrc/backend/kernel_compiler/gpu/cuda_impl/sponge/nvtit/md_iteration_leap_frog_impl.cu
View File

@ -97,9 +97,6 @@ void MDIterationLeapFrog(const int float4_numbers, const int atom_numbers, const
const float exp_gamma, const int is_max_velocity, const float max_velocity,
const float *d_mass_inverse, const float *d_sqrt_mass, float *vel_f, float *crd_f,
float *frc_f, float *acc_f, cudaStream_t stream) {
Reset_List<<<ceilf(static_cast<float>(3. * atom_numbers) / 128), 128>>>(3 * atom_numbers, vel_f, 0.);
Reset_List<<<ceilf(static_cast<float>(3. * atom_numbers) / 128), 128>>>(3 * atom_numbers, crd_f, 0.);
Reset_List<<<ceilf(static_cast<float>(3. * atom_numbers) / 128), 128>>>(3 * atom_numbers, frc_f, 0.);
Reset_List<<<ceilf(static_cast<float>(3. * atom_numbers) / 128), 128>>>(3 * atom_numbers, acc_f, 0.);
VECTOR *frc = const_cast<VECTOR *>(reinterpret_cast<const VECTOR *>(frc_f));

2
mindspore/ccsrc/backend/kernel_compiler/gpu/cuda_impl/sponge/pme/pme_excluded_force_impl.cu
View File

@ -86,7 +86,7 @@ __global__ void PME_Excluded_Force_Correction(const int atom_numbers, const UNSI
void PMEExcludedForce(const int atom_numbers, const float pme_beta, const int *uint_crd_f, const float *sacler_f,
const float *charge, const int *excluded_list_start, const int *excluded_list,
const int *excluded_atom_numbers, float *frc_f, cudaStream_t stream) {
Reset_List<<<ceilf(static_cast<float>(3. * atom_numbers) / 128), 128>>>(3 * atom_numbers, frc_f, 0.);
Reset_List<<<ceilf(static_cast<float>(3. * atom_numbers) / 128), 128, 0, stream>>>(3 * atom_numbers, frc_f, 0.);
UNSIGNED_INT_VECTOR *uint_crd =
const_cast<UNSIGNED_INT_VECTOR *>(reinterpret_cast<const UNSIGNED_INT_VECTOR *>(uint_crd_f));
VECTOR *frc = reinterpret_cast<VECTOR *>(frc_f);

2
mindspore/ccsrc/backend/kernel_compiler/gpu/cuda_impl/sponge/pme/pme_reciprocal_force_impl.cu
View File

@ -75,7 +75,7 @@ void PMEReciprocalForce(int fftx, int ffty, int fftz, int atom_numbers, float be
float *pme_frxyz, float *PME_Q, float *pme_fq, int *PME_atom_near, int *pme_kxyz,
const float *box_length_f, const int *uint_crd_f, const float *charge, float *force,
cudaStream_t stream) {
Reset_List<<<ceilf(static_cast<float>(3. * atom_numbers) / 128), 128>>>(3 * atom_numbers, force, 0.);
Reset_List<<<ceilf(static_cast<float>(3. * atom_numbers) / 128), 128, 0, stream>>>(3 * atom_numbers, force, 0.);
UNSIGNED_INT_VECTOR *uint_crd =
const_cast<UNSIGNED_INT_VECTOR *>(reinterpret_cast<const UNSIGNED_INT_VECTOR *>(uint_crd_f));
UNSIGNED_INT_VECTOR *PME_uxyz = reinterpret_cast<UNSIGNED_INT_VECTOR *>(pme_uxyz);

16
mindspore/ccsrc/backend/kernel_compiler/gpu/sponge/nb14/dihedral_14_cf_energy_kernel.h
View File

@ -64,7 +64,7 @@ class Dihedral14CFEnergyGpuKernel : public GpuKernel {
const std::vector<size_t> &GetOutputSizeList() const override { return output_size_list_; }
const std::vector<size_t> &GetWorkspaceSizeList() const override { return workspace_size_list_; }
bool Launch(const std::vector<AddressPtr> &inputs, const std::vector<AddressPtr> &,
bool Launch(const std::vector<AddressPtr> &inputs, const std::vector<AddressPtr> &workspace,
const std::vector<AddressPtr> &outputs, void *stream_ptr) override {
auto uint_crd_f = GetDeviceAddress<const T1>(inputs, 0);
auto LJtype = GetDeviceAddress<const T1>(inputs, 1);
@ -74,9 +74,10 @@ class Dihedral14CFEnergyGpuKernel : public GpuKernel {
auto b_14 = GetDeviceAddress<const T1>(inputs, 5);
auto cf_scale_factor = GetDeviceAddress<T>(inputs, 6);
auto ene = GetDeviceAddress<T>(outputs, 0);
auto uint_crd_with_LJ = GetDeviceAddress<T>(workspace, 0);
Dihedral14CFEnergy(dihedral_14_numbers, atom_numbers, uint_crd_f, LJtype, charge, boxlength_f, a_14, b_14,
cf_scale_factor, ene, reinterpret_cast<cudaStream_t>(stream_ptr));
Dihedral14CFEnergy(dihedral_14_numbers, atom_numbers, uint_crd_f, LJtype, charge, uint_crd_with_LJ, boxlength_f,
a_14, b_14, cf_scale_factor, ene, reinterpret_cast<cudaStream_t>(stream_ptr));
return true;
}
@ -90,7 +91,7 @@ class Dihedral14CFEnergyGpuKernel : public GpuKernel {
input_size_list_.push_back(ele_a_14 * sizeof(T1));
input_size_list_.push_back(ele_b_14 * sizeof(T1));
input_size_list_.push_back(ele_cf_scale_factor * sizeof(T));
workspace_size_list_.push_back(atom_numbers * sizeof(UINT_VECTOR_LJ_TYPE));
output_size_list_.push_back(atom_numbers * sizeof(T));
}
@ -108,6 +109,13 @@ class Dihedral14CFEnergyGpuKernel : public GpuKernel {
std::vector<size_t> workspace_size_list_;
int dihedral_14_numbers;
int atom_numbers;
struct UINT_VECTOR_LJ_TYPE {
unsigned int uint_x;
unsigned int uint_y;
unsigned int uint_z;
int LJ_type;
float charge;
};
};
} // namespace kernel
} // namespace mindspore

18
mindspore/ccsrc/backend/kernel_compiler/gpu/sponge/nb14/dihedral_14_lj_cf_force_with_atom_energy_kernel.h
View File

@ -70,7 +70,7 @@ class Dihedral14LJCFForceWithAtomEnergyGpuKernel : public GpuKernel {
const std::vector<size_t> &GetOutputSizeList() const override { return output_size_list_; }
const std::vector<size_t> &GetWorkspaceSizeList() const override { return workspace_size_list_; }
bool Launch(const std::vector<AddressPtr> &inputs, const std::vector<AddressPtr> &,
bool Launch(const std::vector<AddressPtr> &inputs, const std::vector<AddressPtr> &workspace,
const std::vector<AddressPtr> &outputs, void *stream_ptr) override {
auto uint_crd_f = GetDeviceAddress<const T1>(inputs, 0);
auto LJtype = GetDeviceAddress<const T1>(inputs, 1);
@ -85,9 +85,11 @@ class Dihedral14LJCFForceWithAtomEnergyGpuKernel : public GpuKernel {
auto frc_f = GetDeviceAddress<T>(outputs, 0);
auto atom_energy = GetDeviceAddress<T>(outputs, 1);
Dihedral14LJCFForceWithAtomEnergy(dihedral_14_numbers, atom_numbers, uint_crd_f, LJtype, charge, boxlength_f, a_14,
b_14, lj_scale_factor, cf_scale_factor, LJ_type_A, LJ_type_B, frc_f, atom_energy,
reinterpret_cast<cudaStream_t>(stream_ptr));
auto uint_crd_with_LJ = GetDeviceAddress<T>(workspace, 0);
Dihedral14LJCFForceWithAtomEnergy(dihedral_14_numbers, atom_numbers, uint_crd_f, LJtype, charge, uint_crd_with_LJ,
boxlength_f, a_14, b_14, lj_scale_factor, cf_scale_factor, LJ_type_A, LJ_type_B,
frc_f, atom_energy, reinterpret_cast<cudaStream_t>(stream_ptr));
return true;
}
@ -104,6 +106,7 @@ class Dihedral14LJCFForceWithAtomEnergyGpuKernel : public GpuKernel {
input_size_list_.push_back(ele_cf_scale_factor * sizeof(T));
input_size_list_.push_back(ele_LJ_type_A * sizeof(T));
input_size_list_.push_back(ele_LJ_type_B * sizeof(T));
workspace_size_list_.push_back(atom_numbers * sizeof(UINT_VECTOR_LJ_TYPE));
output_size_list_.push_back(3 * atom_numbers * sizeof(T));
output_size_list_.push_back(atom_numbers * sizeof(T));
@ -126,6 +129,13 @@ class Dihedral14LJCFForceWithAtomEnergyGpuKernel : public GpuKernel {
std::vector<size_t> workspace_size_list_;
int dihedral_14_numbers;
int atom_numbers;
struct UINT_VECTOR_LJ_TYPE {
unsigned int uint_x;
unsigned int uint_y;
unsigned int uint_z;
int LJ_type;
float charge;
};
};
} // namespace kernel
} // namespace mindspore

16
mindspore/ccsrc/backend/kernel_compiler/gpu/sponge/nb14/dihedral_14_lj_energy_kernel.h
View File

@ -68,7 +68,7 @@ class Dihedral14LJEnergyGpuKernel : public GpuKernel {
const std::vector<size_t> &GetOutputSizeList() const override { return output_size_list_; }
const std::vector<size_t> &GetWorkspaceSizeList() const override { return workspace_size_list_; }
bool Launch(const std::vector<AddressPtr> &inputs, const std::vector<AddressPtr> &,
bool Launch(const std::vector<AddressPtr> &inputs, const std::vector<AddressPtr> &workspace,
const std::vector<AddressPtr> &outputs, void *stream_ptr) override {
auto uint_crd_f = GetDeviceAddress<const T1>(inputs, 0);
auto LJtype = GetDeviceAddress<const T1>(inputs, 1);
@ -80,9 +80,11 @@ class Dihedral14LJEnergyGpuKernel : public GpuKernel {
auto LJ_type_A = GetDeviceAddress<T>(inputs, 7);
auto LJ_type_B = GetDeviceAddress<T>(inputs, 8);
auto ene = GetDeviceAddress<T>(outputs, 0);
auto uint_crd_with_LJ = GetDeviceAddress<T>(workspace, 0);
Dihedral14LJEnergy(dihedral_14_numbers, atom_numbers, uint_crd_f, LJtype, charge, boxlength_f, a_14, b_14,
lj_scale_factor, LJ_type_A, LJ_type_B, ene, reinterpret_cast<cudaStream_t>(stream_ptr));
Dihedral14LJEnergy(dihedral_14_numbers, atom_numbers, uint_crd_f, LJtype, charge, uint_crd_with_LJ, boxlength_f,
a_14, b_14, lj_scale_factor, LJ_type_A, LJ_type_B, ene,
reinterpret_cast<cudaStream_t>(stream_ptr));
return true;
}
@ -98,6 +100,7 @@ class Dihedral14LJEnergyGpuKernel : public GpuKernel {
input_size_list_.push_back(ele_lj_scale_factor * sizeof(T));
input_size_list_.push_back(ele_LJ_type_A * sizeof(T));
input_size_list_.push_back(ele_LJ_type_B * sizeof(T));
workspace_size_list_.push_back(atom_numbers * sizeof(UINT_VECTOR_LJ_TYPE));
output_size_list_.push_back(atom_numbers * sizeof(T));
}
@ -118,6 +121,13 @@ class Dihedral14LJEnergyGpuKernel : public GpuKernel {
std::vector<size_t> workspace_size_list_;
int dihedral_14_numbers;
int atom_numbers;
struct UINT_VECTOR_LJ_TYPE {
unsigned int uint_x;
unsigned int uint_y;
unsigned int uint_z;
int LJ_type;
float charge;
};
};
} // namespace kernel
} // namespace mindspore

3
mindspore/ccsrc/backend/kernel_compiler/gpu/sponge/pme/pme_energy_kernel.h
View File

@ -93,7 +93,7 @@ class PMEEnergyGpuKernel : public GpuKernel {
input_size_list_.push_back(atom_numbers * sizeof(VECTOR));
input_size_list_.push_back(atom_numbers * sizeof(T1));
input_size_list_.push_back(atom_numbers * sizeof(T1));
input_size_list_.push_back(excluded_numbers * sizeof(T1));
input_size_list_.push_back(atom_numbers * sizeof(T1));
workspace_size_list_.push_back(atom_numbers * sizeof(UNSIGNED_INT_VECTOR));
@ -118,6 +118,7 @@ class PMEEnergyGpuKernel : public GpuKernel {
std::vector<size_t> output_size_list_;
std::vector<size_t> workspace_size_list_;
int atom_numbers;
int excluded_numbers = 2719;
int max_nl_numbers = 800;
int fftx;
int ffty;

3
mindspore/ccsrc/backend/kernel_compiler/gpu/sponge/pme/pme_excluded_force_kernel.h
View File

@ -65,7 +65,7 @@ class PMEExcludedForceGpuKernel : public GpuKernel {
input_size_list_.push_back(atom_numbers * sizeof(VECTOR));
input_size_list_.push_back(atom_numbers * sizeof(T));
input_size_list_.push_back(atom_numbers * sizeof(T1));
input_size_list_.push_back(atom_numbers * sizeof(T1));
input_size_list_.push_back(excluded_numbers * sizeof(T1));
input_size_list_.push_back(atom_numbers * sizeof(T1));
output_size_list_.push_back(atom_numbers * 3 * sizeof(T));
@ -77,6 +77,7 @@ class PMEExcludedForceGpuKernel : public GpuKernel {
std::vector<size_t> output_size_list_;
std::vector<size_t> workspace_size_list_;
int atom_numbers;
int excluded_numbers = 2719;
float beta;
struct VECTOR {
float x;

429
mindspore/ops/operations/sponge_ops.py
View File

@ -29,6 +29,9 @@ class BondForce(PrimitiveWithInfer):
.. math::
dr = (x_1-x_2, y_1-y_2, z_1-z_2)
.. math::
F = (F_x, F_y, F_z) = 2*k*(1 - r_0/|dr|)*dr
Args:
@ -53,8 +56,8 @@ class BondForce(PrimitiveWithInfer):
@prim_attr_register
def __init__(self, bond_numbers, atom_numbers):
assert isinstance(bond_numbers, int)
assert isinstance(atom_numbers, int)
validator.check_value_type('bond_numbers', bond_numbers, (int), self.name)
validator.check_value_type('atom_numbers', atom_numbers, (int), self.name)
self.bond_numbers = bond_numbers
self.atom_numbers = atom_numbers
self.add_prim_attr('bond_numbers', self.bond_numbers)
@ -66,8 +69,8 @@ class BondForce(PrimitiveWithInfer):
cls_name = self.name
N = self.atom_numbers
M = self.bond_numbers
validator.check_int(uint_crd_f_shape[0], N, Rel.EQ, "uint_crd_f", cls_name)
validator.check_int(uint_crd_f_shape[1], 3, Rel.EQ, "uint_crd_f", cls_name)
validator.check_int(uint_crd_f_shape[0], N, Rel.EQ, "uint_crd_f[0]", cls_name)
validator.check_int(uint_crd_f_shape[1], 3, Rel.EQ, "uint_crd_f[1]", cls_name)
validator.check_int(scaler_f_shape[0], 3, Rel.EQ, "scaler_f", cls_name)
validator.check_int(atom_a_shape[0], M, Rel.EQ, "uint_crd_f", cls_name)
validator.check_int(atom_b_shape[0], M, Rel.EQ, "atom_b", cls_name)
@ -93,6 +96,9 @@ class BondEnergy(PrimitiveWithInfer):
.. math::
dr = (x_1-x_2, y_1-y_2, z_1-z_2)
.. math::
E = k*(|dr| - r_0)^2
Args:
@ -117,8 +123,8 @@ class BondEnergy(PrimitiveWithInfer):
@prim_attr_register
def __init__(self, bond_numbers, atom_numbers):
assert isinstance(bond_numbers, int)
assert isinstance(atom_numbers, int)
validator.check_value_type('bond_numbers', bond_numbers, (int), self.name)
validator.check_value_type('atom_numbers', atom_numbers, (int), self.name)
self.bond_numbers = bond_numbers
self.atom_numbers = atom_numbers
self.add_prim_attr('bond_numbers', self.bond_numbers)
@ -130,8 +136,8 @@ class BondEnergy(PrimitiveWithInfer):
cls_name = self.name
N = self.atom_numbers
M = self.bond_numbers
validator.check_int(uint_crd_f_shape[0], N, Rel.EQ, "uint_crd_f", cls_name)
validator.check_int(uint_crd_f_shape[1], 3, Rel.EQ, "uint_crd_f", cls_name)
validator.check_int(uint_crd_f_shape[0], N, Rel.EQ, "uint_crd_f[0]", cls_name)
validator.check_int(uint_crd_f_shape[1], 3, Rel.EQ, "uint_crd_f[1]", cls_name)
validator.check_int(scaler_f_shape[0], 3, Rel.EQ, "scaler_f", cls_name)
validator.check_int(atom_a_shape[0], M, Rel.EQ, "uint_crd_f", cls_name)
validator.check_int(atom_b_shape[0], M, Rel.EQ, "atom_b", cls_name)
@ -179,8 +185,8 @@ class BondAtomEnergy(PrimitiveWithInfer):
@prim_attr_register
def __init__(self, bond_numbers, atom_numbers):
assert isinstance(bond_numbers, int)
assert isinstance(atom_numbers, int)
validator.check_value_type('bond_numbers', bond_numbers, (int), self.name)
validator.check_value_type('atom_numbers', atom_numbers, (int), self.name)
self.bond_numbers = bond_numbers
self.atom_numbers = atom_numbers
self.add_prim_attr('bond_numbers', self.bond_numbers)
@ -192,8 +198,8 @@ class BondAtomEnergy(PrimitiveWithInfer):
cls_name = self.name
N = self.atom_numbers
M = self.bond_numbers
validator.check_int(uint_crd_f_shape[0], N, Rel.EQ, "uint_crd_f", cls_name)
validator.check_int(uint_crd_f_shape[1], 3, Rel.EQ, "uint_crd_f", cls_name)
validator.check_int(uint_crd_f_shape[0], N, Rel.EQ, "uint_crd_f[0]", cls_name)
validator.check_int(uint_crd_f_shape[1], 3, Rel.EQ, "uint_crd_f[1]", cls_name)
validator.check_int(scaler_f_shape[0], 3, Rel.EQ, "scaler_f", cls_name)
validator.check_int(atom_a_shape[0], M, Rel.EQ, "uint_crd_f", cls_name)
validator.check_int(atom_b_shape[0], M, Rel.EQ, "atom_b", cls_name)
@ -240,8 +246,8 @@ class BondForceWithAtomEnergy(PrimitiveWithInfer):
@prim_attr_register
def __init__(self, bond_numbers, atom_numbers):
assert isinstance(bond_numbers, int)
assert isinstance(atom_numbers, int)
validator.check_value_type('bond_numbers', bond_numbers, (int), self.name)
validator.check_value_type('atom_numbers', atom_numbers, (int), self.name)
self.bond_numbers = bond_numbers
self.atom_numbers = atom_numbers
self.add_prim_attr('bond_numbers', self.bond_numbers)
@ -253,8 +259,8 @@ class BondForceWithAtomEnergy(PrimitiveWithInfer):
cls_name = self.name
N = self.atom_numbers
M = self.bond_numbers
validator.check_int(uint_crd_f_shape[0], N, Rel.EQ, "uint_crd_f", cls_name)
validator.check_int(uint_crd_f_shape[1], 3, Rel.EQ, "uint_crd_f", cls_name)
validator.check_int(uint_crd_f_shape[0], N, Rel.EQ, "uint_crd_f[0]", cls_name)
validator.check_int(uint_crd_f_shape[1], 3, Rel.EQ, "uint_crd_f[1]", cls_name)
validator.check_int(scaler_f_shape[0], 3, Rel.EQ, "scaler_f", cls_name)
validator.check_int(atom_a_shape[0], M, Rel.EQ, "uint_crd_f", cls_name)
validator.check_int(atom_b_shape[0], M, Rel.EQ, "atom_b", cls_name)
@ -286,6 +292,9 @@ class BondForceWithAtomVirial(PrimitiveWithInfer):
.. math::
dr = (x_1-x_2, y_1-y_2, z_1-z_2)
.. math::
virial = |dr|*(|dr| - r_0)*k
Args:
@ -311,8 +320,8 @@ class BondForceWithAtomVirial(PrimitiveWithInfer):
@prim_attr_register
def __init__(self, bond_numbers, atom_numbers):
assert isinstance(bond_numbers, int)
assert isinstance(atom_numbers, int)
validator.check_value_type('bond_numbers', bond_numbers, (int), self.name)
validator.check_value_type('atom_numbers', atom_numbers, (int), self.name)
self.bond_numbers = bond_numbers
self.atom_numbers = atom_numbers
self.add_prim_attr('bond_numbers', self.bond_numbers)
@ -324,8 +333,8 @@ class BondForceWithAtomVirial(PrimitiveWithInfer):
cls_name = self.name
N = self.atom_numbers
M = self.bond_numbers
validator.check_int(uint_crd_f_shape[0], N, Rel.EQ, "uint_crd_f", cls_name)
validator.check_int(uint_crd_f_shape[1], 3, Rel.EQ, "uint_crd_f", cls_name)
validator.check_int(uint_crd_f_shape[0], N, Rel.EQ, "uint_crd_f[0]", cls_name)
validator.check_int(uint_crd_f_shape[1], 3, Rel.EQ, "uint_crd_f[1]", cls_name)
validator.check_int(scaler_f_shape[0], 3, Rel.EQ, "scaler_f", cls_name)
validator.check_int(atom_a_shape[0], M, Rel.EQ, "uint_crd_f", cls_name)
validator.check_int(atom_b_shape[0], M, Rel.EQ, "atom_b", cls_name)
@ -355,25 +364,36 @@ class DihedralForce(PrimitiveWithInfer):
.. math::
dr_{ab} = (x_b-x_a, y_b-y_a, z_b-z_a)
.. math::
dr_{cb} = (x_b-x_c, y_b-y_c, z_b-z_c)
.. math::
dr_{cd} = (x_d-x_c, y_d-y_c, z_d-z_c)
.. math::
r1 = dr_{ab}*dr_{cb}
.. math::
r2 = dr_{cd}*dr_{cb}
.. math::
phi = pi - sign(inner_product(r1*r2), dr_{cb})
* arccos(inner_product(r1, r2)/|r1|/|r2|)
.. math::
dEdphi = n*phi*(k*cos(phi_0)*sin(n*phi) - k*sin(phi_0)*cos(n*phi))/sin(phi)
.. math::
dphidr1 = r2/|r1|/|r2| + cos(phi)/|r1|^2*r1
.. math::
dphidr2 = r1/|r1|/|r2| + cos(phi)/|r2|^2*r2
.. math::
dEdra = dEdphi * dr_{cb} * dphidr1
.. math::
dEdrd = dEdphi * dphi_dr2 * dr_{cb}
.. math::
dEdrjpart = dEdphi * ((dr_{ab} * dphidr1) + (dr_{cd} * dphidr2))
.. math::
F_a = dEdri
.. math::
F_b = dEdrjpart - dEdri
.. math::
F_c = - dEdrl - dEdrjpart
.. math::
F_d = dEdrl
Args:
@ -405,7 +425,7 @@ class DihedralForce(PrimitiveWithInfer):
@prim_attr_register
def __init__(self, dihedral_numbers):
assert isinstance(dihedral_numbers, int)
validator.check_value_type('dihedral_numbers', dihedral_numbers, (int), self.name)
self.dihedral_numbers = dihedral_numbers
self.init_prim_io_names(inputs=['uint_crd_f', 'scaler_f', 'atom_a', 'atom_b', 'atom_c', 'atom_d', 'ipn', 'pk',
'gamc', 'gams', 'pn'],
@ -415,8 +435,8 @@ class DihedralForce(PrimitiveWithInfer):
def infer_shape(self, uint_crd_f_shape, scaler_f_shape, atom_a_shape, atom_b_shape, atom_c_shape, atom_d_shape,
ipn_shape, pk_shape, gamc_shape, gams_shape, pn_shape):
cls_name = self.name
M = atom_a_shape[0]
validator.check_int(uint_crd_f_shape[1], 3, Rel.EQ, "uint_crd_f", cls_name)
M = self.dihedral_numbers
validator.check_int(uint_crd_f_shape[1], 3, Rel.EQ, "uint_crd_f[1]", cls_name)
validator.check_int(scaler_f_shape[0], 3, Rel.EQ, "scaler_f", cls_name)
validator.check_int(atom_a_shape[0], M, Rel.EQ, "atom_a", cls_name)
validator.check_int(atom_b_shape[0], M, Rel.EQ, "atom_b", cls_name)
@ -485,7 +505,7 @@ class DihedralEnergy(PrimitiveWithInfer):
@prim_attr_register
def __init__(self, dihedral_numbers):
assert isinstance(dihedral_numbers, int)
validator.check_value_type('dihedral_numbers', dihedral_numbers, (int), self.name)
self.dihedral_numbers = dihedral_numbers
self.init_prim_io_names(inputs=['uint_crd_f', 'scaler_f', 'atom_a', 'atom_b', 'atom_c', 'atom_d', 'ipn', 'pk',
'gamc', 'gams', 'pn'],
@ -495,8 +515,8 @@ class DihedralEnergy(PrimitiveWithInfer):
def infer_shape(self, uint_crd_f_shape, scaler_f_shape, atom_a_shape, atom_b_shape, atom_c_shape, atom_d_shape,
ipn_shape, pk_shape, gamc_shape, gams_shape, pn_shape):
cls_name = self.name
M = atom_a_shape[0]
validator.check_int(uint_crd_f_shape[1], 3, Rel.EQ, "uint_crd_f", cls_name)
M = self.dihedral_numbers
validator.check_int(uint_crd_f_shape[1], 3, Rel.EQ, "uint_crd_f[1]", cls_name)
validator.check_int(scaler_f_shape[0], 3, Rel.EQ, "scaler_f", cls_name)
validator.check_int(atom_a_shape[0], M, Rel.EQ, "atom_a", cls_name)
validator.check_int(atom_b_shape[0], M, Rel.EQ, "atom_b", cls_name)
@ -563,7 +583,7 @@ class DihedralAtomEnergy(PrimitiveWithInfer):
@prim_attr_register
def __init__(self, dihedral_numbers):
assert isinstance(dihedral_numbers, int)
validator.check_value_type('dihedral_numbers', dihedral_numbers, (int), self.name)
self.dihedral_numbers = dihedral_numbers
self.init_prim_io_names(inputs=['uint_crd_f', 'scaler_f', 'atom_a', 'atom_b', 'atom_c', 'atom_d', 'ipn', 'pk',
'gamc', 'gams', 'pn'],
@ -574,8 +594,8 @@ class DihedralAtomEnergy(PrimitiveWithInfer):
ipn_shape, pk_shape, gamc_shape, gams_shape, pn_shape):
cls_name = self.name
N = uint_crd_f_shape[0]
M = atom_a_shape[0]
validator.check_int(uint_crd_f_shape[1], 3, Rel.EQ, "uint_crd_f", cls_name)
M = self.dihedral_numbers
validator.check_int(uint_crd_f_shape[1], 3, Rel.EQ, "uint_crd_f[1]", cls_name)
validator.check_int(scaler_f_shape[0], 3, Rel.EQ, "scaler_f", cls_name)
validator.check_int(atom_a_shape[0], M, Rel.EQ, "atom_a", cls_name)
validator.check_int(atom_b_shape[0], M, Rel.EQ, "atom_b", cls_name)
@ -641,7 +661,7 @@ class DihedralForceWithAtomEnergy(PrimitiveWithInfer):
@prim_attr_register
def __init__(self, dihedral_numbers):
assert isinstance(dihedral_numbers, int)
validator.check_value_type('dihedral_numbers', dihedral_numbers, (int), self.name)
self.dihedral_numbers = dihedral_numbers
self.init_prim_io_names(inputs=['uint_crd_f', 'scaler_f', 'atom_a', 'atom_b', 'atom_c', 'atom_d', 'ipn', 'pk',
'gamc', 'gams', 'pn'],
@ -652,8 +672,8 @@ class DihedralForceWithAtomEnergy(PrimitiveWithInfer):
ipn_shape, pk_shape, gamc_shape, gams_shape, pn_shape):
cls_name = self.name
N = uint_crd_f_shape[0]
M = atom_a_shape[0]
validator.check_int(uint_crd_f_shape[1], 3, Rel.EQ, "uint_crd_f", cls_name)
M = self.dihedral_numbers
validator.check_int(uint_crd_f_shape[1], 3, Rel.EQ, "uint_crd_f[1]", cls_name)
validator.check_int(scaler_f_shape[0], 3, Rel.EQ, "scaler_f", cls_name)
validator.check_int(atom_a_shape[0], M, Rel.EQ, "atom_a", cls_name)
validator.check_int(atom_b_shape[0], M, Rel.EQ, "atom_b", cls_name)
@ -690,14 +710,18 @@ class AngleForce(PrimitiveWithInfer):
number of atoms is N.
.. math::
dr_{ab} = (x_b-x_a, y_b-y_a, z_b-z_a)
.. math::
dr_{cb} = (x_b-x_c, y_b-y_c, z_b-z_c)
.. math::
theta = arccos(inner_product(dr_{ab}, dr_{cb})/|dr_{ab}|/|dr_{cb}|)
.. math::
F_a = -2*k*(theta-theta_0)/sin(theta)*[cos(theta)/|dr_{ab}|^2*dr_{ab}
- 1/|dr_{ab}|/|dr_{cb}|*dr_{cb}]
.. math::
F_c = -2*k*(theta-theta_0)/sin(theta)*[cos(theta)/|dr_{cb}|^2*dr_{cb}
- 1/|dr_{cb}|/|dr_{ab}|*dr_{ab}]
.. math::
F_b = -F_a - F_c
Args:
@ -722,7 +746,7 @@ class AngleForce(PrimitiveWithInfer):
@prim_attr_register
def __init__(self, angle_numbers):
assert isinstance(angle_numbers, int)
validator.check_value_type('angle_numbers', angle_numbers, (int), self.name)
self.angle_numbers = angle_numbers
self.init_prim_io_names(inputs=['uint_crd_f', 'scaler_f', 'atom_a', 'atom_b', 'atom_c', 'angle_k',
'angle_theta0'],
@ -732,8 +756,8 @@ class AngleForce(PrimitiveWithInfer):
def infer_shape(self, uint_crd_f_shape, scaler_f_shape, atom_a_shape, atom_b_shape, atom_c_shape, angle_k_shape,
angle_theta0_shape):
cls_name = self.name
M = atom_a_shape[0]
validator.check_int(uint_crd_f_shape[1], 3, Rel.EQ, "uint_crd_f", cls_name)
M = self.angle_numbers
validator.check_int(uint_crd_f_shape[1], 3, Rel.EQ, "uint_crd_f[1]", cls_name)
validator.check_int(scaler_f_shape[0], 3, Rel.EQ, "scaler_f", cls_name)
validator.check_int(atom_a_shape[0], M, Rel.EQ, "atom_a", cls_name)
validator.check_int(atom_b_shape[0], M, Rel.EQ, "atom_b", cls_name)
@ -756,13 +780,16 @@ class AngleForce(PrimitiveWithInfer):
class AngleEnergy(PrimitiveWithInfer):
"""
Calculate the energy caused by 3-atoms angle term.
Calculate the energy caused by 3-atoms angle term. Assume the number of angles is M and the
number of atoms is N.
.. math::
dr_{ab} = (x_b-x_a, y_b-y_a, z_b-z_a)
.. math::
dr_{cb} = (x_b-x_c, y_b-y_c, z_b-z_c)
.. math::
theta = arccos(inner_product(dr_{ab}, dr_{cb})/|dr_{ab}|/|dr_{cb}|)
.. math::
E = k*(theta - theta_0)^2
Args:
@ -787,7 +814,7 @@ class AngleEnergy(PrimitiveWithInfer):
@prim_attr_register
def __init__(self, angle_numbers):
assert isinstance(angle_numbers, int)
validator.check_value_type('angle_numbers', angle_numbers, (int), self.name)
self.angle_numbers = angle_numbers
self.init_prim_io_names(inputs=['uint_crd_f', 'scaler_f', 'atom_a', 'atom_b', 'atom_c', 'angle_k',
'angle_theta0'],
@ -797,8 +824,8 @@ class AngleEnergy(PrimitiveWithInfer):
def infer_shape(self, uint_crd_f_shape, scaler_f_shape, atom_a_shape, atom_b_shape, atom_c_shape, angle_k_shape,
angle_theta0_shape):
cls_name = self.name
M = atom_a_shape[0]
validator.check_int(uint_crd_f_shape[1], 3, Rel.EQ, "uint_crd_f", cls_name)
M = self.angle_numbers
validator.check_int(uint_crd_f_shape[1], 3, Rel.EQ, "uint_crd_f[1]", cls_name)
validator.check_int(scaler_f_shape[0], 3, Rel.EQ, "scaler_f", cls_name)
validator.check_int(atom_a_shape[0], M, Rel.EQ, "atom_a", cls_name)
validator.check_int(atom_b_shape[0], M, Rel.EQ, "atom_b", cls_name)
@ -822,7 +849,8 @@ class AngleEnergy(PrimitiveWithInfer):
class AngleAtomEnergy(PrimitiveWithInfer):
"""
Add the potential energy caused by angle terms to the total potential
energy of each atom.
energy of each atom. Assume the number of angles is M and the
number of atoms is N.
The calculation formula is the same as operator AngleEnergy().
@ -848,7 +876,7 @@ class AngleAtomEnergy(PrimitiveWithInfer):
@prim_attr_register
def __init__(self, angle_numbers):
assert isinstance(angle_numbers, int)
validator.check_value_type('angle_numbers', angle_numbers, (int), self.name)
self.angle_numbers = angle_numbers
self.init_prim_io_names(inputs=['uint_crd_f', 'scaler_f', 'atom_a', 'atom_b', 'atom_c', 'angle_k',
'angle_theta0'],
@ -859,8 +887,8 @@ class AngleAtomEnergy(PrimitiveWithInfer):
angle_theta0_shape):
cls_name = self.name
N = uint_crd_f_shape[0]
M = atom_a_shape[0]
validator.check_int(uint_crd_f_shape[1], 3, Rel.EQ, "uint_crd_f", cls_name)
M = self.angle_numbers
validator.check_int(uint_crd_f_shape[1], 3, Rel.EQ, "uint_crd_f[1]", cls_name)
validator.check_int(scaler_f_shape[0], 3, Rel.EQ, "scaler_f", cls_name)
validator.check_int(atom_a_shape[0], M, Rel.EQ, "atom_a", cls_name)
validator.check_int(atom_b_shape[0], M, Rel.EQ, "atom_b", cls_name)
@ -883,7 +911,8 @@ class AngleAtomEnergy(PrimitiveWithInfer):
class AngleForceWithAtomEnergy(PrimitiveWithInfer):
"""
Calculate angle force and potential energy together.
Calculate angle force and potential energy together. Assume the number of angles is M and the
number of atoms is N.
The calculation formula is the same as operator AngleForce() and AngleEnergy().
@ -910,7 +939,7 @@ class AngleForceWithAtomEnergy(PrimitiveWithInfer):
@prim_attr_register
def __init__(self, angle_numbers):
assert isinstance(angle_numbers, int)
validator.check_value_type('angle_numbers', angle_numbers, (int), self.name)
self.angle_numbers = angle_numbers
self.init_prim_io_names(inputs=['uint_crd_f', 'scaler_f', 'atom_a', 'atom_b', 'atom_c', 'angle_k',
'angle_theta0'],
@ -921,8 +950,8 @@ class AngleForceWithAtomEnergy(PrimitiveWithInfer):
angle_theta0_shape):
cls_name = self.name
N = uint_crd_f_shape[0]
M = atom_a_shape[0]
validator.check_int(uint_crd_f_shape[1], 3, Rel.EQ, "uint_crd_f", cls_name)
M = self.angle_numbers
validator.check_int(uint_crd_f_shape[1], 3, Rel.EQ, "uint_crd_f[1]", cls_name)
validator.check_int(scaler_f_shape[0], 3, Rel.EQ, "scaler_f", cls_name)
validator.check_int(atom_a_shape[0], M, Rel.EQ, "atom_a", cls_name)
validator.check_int(atom_b_shape[0], M, Rel.EQ, "atom_b", cls_name)
@ -954,8 +983,8 @@ class Dihedral14LJForce(PrimitiveWithInfer):
for all kinds of atom pairs.
.. math::
dr = (x_a-x_b, y_a-y_b, z_a-z_b)
.. math::
F = k*(-12*A/|dr|^{14} + 6*B/|dr|^{8})*dr
Args:
@ -972,7 +1001,9 @@ class Dihedral14LJForce(PrimitiveWithInfer):
- **lj_scale_factor** (Tensor, float32) - [M,], the scale factor for the
Lennard-Jones part of force correction of each dihedral 1,4 term.
- **LJ_type_A** (Tensor, float32) - [Q,], the A parameter in Lennard-Jones scheme of each atom pair type.
Q is the number of atom pair.
- **LJ_type_B** (Tensor, float32) - [Q,], the B parameter in Lennard-Jones shceme of each atom pair type.
Q is the number of atom pair.
Outputs:
- **frc_f** (Tensor, float32) - [N, 3], the force felt by each atom.
@ -983,8 +1014,8 @@ class Dihedral14LJForce(PrimitiveWithInfer):
@prim_attr_register
def __init__(self, nb14_numbers, atom_numbers):
assert isinstance(nb14_numbers, int)
assert isinstance(atom_numbers, int)
validator.check_value_type('nb14_numbers', nb14_numbers, (int), self.name)
validator.check_value_type('atom_numbers', atom_numbers, (int), self.name)
self.dihedral_14_numbers = nb14_numbers
self.atom_numbers = atom_numbers
self.init_prim_io_names(
@ -996,6 +1027,19 @@ class Dihedral14LJForce(PrimitiveWithInfer):
def infer_shape(self, uint_crd_f_shape, LJtype_shape, charge_shape, boxlength_f_shape, a_14_shape, b_14_shape,
lj_scale_factor_shape, LJ_type_A_shape, LJ_type_B_shape):
cls_name = self.name
N = self.atom_numbers
M = self.dihedral_14_numbers
Q = LJ_type_A_shape[0]
validator.check_int(uint_crd_f_shape[0], N, Rel.EQ, "uint_crd_f[0]", cls_name)
validator.check_int(uint_crd_f_shape[1], 3, Rel.EQ, "uint_crd_f[1]", cls_name)
validator.check_int(LJtype_shape[0], 3, Rel.EQ, "LJtype", cls_name)
validator.check_int(charge_shape[0], M, Rel.EQ, "charge", cls_name)
validator.check_int(boxlength_f_shape[0], 3, Rel.EQ, "boxlength_f", cls_name)
validator.check_int(a_14_shape[0], M, Rel.EQ, "a_14", cls_name)
validator.check_int(b_14_shape[0], M, Rel.EQ, "b_14", cls_name)
validator.check_int(lj_scale_factor_shape[0], M, Rel.EQ, "lj_scale_factor", cls_name)
validator.check_int(LJ_type_B_shape[0], Q, Rel.EQ, "LJ_type_B", cls_name)
return uint_crd_f_shape
def infer_dtype(self, uint_crd_f_dtype, LJtype_dtype, charge_dtype, boxlength_f_type, a_14_type, b_14_type,
@ -1019,9 +1063,9 @@ class Dihedral14LJEnergy(PrimitiveWithInfer):
Calculate the Lennard-Jones part of 1,4 dihedral energy correction for
each necessary dihedral terms on the corresponding atoms.
.. math:, the :
.. math::
dr = (x_a-x_b, y_a-y_b, z_a-z-b)
.. math::
E = k*(A/|dr|^{12} - B/|dr|^{6})
Args:
@ -1038,7 +1082,9 @@ class Dihedral14LJEnergy(PrimitiveWithInfer):
- **lj_scale_factor** (Tensor, float32) - [M,], the scale factor for the
Lennard-Jones part of force correction of each dihedral 1,4 term.
- **LJ_type_A** (Tensor, float32) - [Q,], the A parameter in Lennard-Jones scheme of each atom pair type.
Q is the number of atom pair.
- **LJ_type_B** (Tensor, float32) - [Q,], the B parameter in Lennard-Jones shceme of each atom pair type.
Q is the number of atom pair.
Outputs:
- **ene** (Tensor, float32) - [M,], the Lennard-Jones potential
@ -1050,8 +1096,8 @@ class Dihedral14LJEnergy(PrimitiveWithInfer):
@prim_attr_register
def __init__(self, nb14_numbers, atom_numbers):
assert isinstance(nb14_numbers, int)
assert isinstance(atom_numbers, int)
validator.check_value_type('nb14_numbers', nb14_numbers, (int), self.name)
validator.check_value_type('atom_numbers', atom_numbers, (int), self.name)
self.dihedral_14_numbers = nb14_numbers
self.atom_numbers = atom_numbers
@ -1064,6 +1110,19 @@ class Dihedral14LJEnergy(PrimitiveWithInfer):
def infer_shape(self, uint_crd_f_shape, LJtype_shape, charge_shape, boxlength_f_shape, a_14_shape, b_14_shape,
lj_scale_factor_shape, LJ_type_A_shape, LJ_type_B_shape):
cls_name = self.name
N = self.atom_numbers
M = self.dihedral_14_numbers
Q = LJ_type_A_shape[0]
validator.check_int(uint_crd_f_shape[0], N, Rel.EQ, "uint_crd_f[0]", cls_name)
validator.check_int(uint_crd_f_shape[1], 3, Rel.EQ, "uint_crd_f[1]", cls_name)
validator.check_int(LJtype_shape[0], 3, Rel.EQ, "LJtype", cls_name)
validator.check_int(charge_shape[0], M, Rel.EQ, "charge", cls_name)
validator.check_int(boxlength_f_shape[0], 3, Rel.EQ, "boxlength_f", cls_name)
validator.check_int(a_14_shape[0], M, Rel.EQ, "a_14", cls_name)
validator.check_int(b_14_shape[0], M, Rel.EQ, "b_14", cls_name)
validator.check_int(lj_scale_factor_shape[0], M, Rel.EQ, "lj_scale_factor", cls_name)
validator.check_int(LJ_type_B_shape[0], Q, Rel.EQ, "LJ_type_B", cls_name)
return [self.dihedral_14_numbers,]
def infer_dtype(self, uint_crd_f_dtype, LJtype_dtype, charge_dtype, boxlength_f_type, a_14_type, b_14_type,
@ -1090,8 +1149,8 @@ class Dihedral14LJForceWithDirectCF(PrimitiveWithInfer):
Dihedral14LJForce(), and the Coulomb part is as follows:
.. math::
dr = (x_a-x_b, y_a-y_b, z_a-z_b)
.. math::
F = -k*q_a*q_b/|r|^3*dr
Args:
@ -1110,7 +1169,9 @@ class Dihedral14LJForceWithDirectCF(PrimitiveWithInfer):
- **cf_scale_factor** (Tensor, float) - [M,], the scale factor for the
Coulomb part of force correction for each dihedral 1,4 terms.
- **LJ_type_A** (Tensor, float32) - [Q,], the A parameter in Lennard-Jones scheme of each atom pair type.
Q is the number of atom pair.
- **LJ_type_B** (Tensor, float32) - [Q,], the B parameter in Lennard-Jones shceme of each atom pair type.
Q is the number of atom pair.
Outputs:
- **frc_f** (Tensor, float) - [N, 3], the force felt by each atom.
@ -1121,8 +1182,8 @@ class Dihedral14LJForceWithDirectCF(PrimitiveWithInfer):
@prim_attr_register
def __init__(self, nb14_numbers, atom_numbers):
assert isinstance(nb14_numbers, int)
assert isinstance(atom_numbers, int)
validator.check_value_type('nb14_numbers', nb14_numbers, (int), self.name)
validator.check_value_type('atom_numbers', atom_numbers, (int), self.name)
self.dihedral_14_numbers = nb14_numbers
self.atom_numbers = atom_numbers
@ -1136,6 +1197,20 @@ class Dihedral14LJForceWithDirectCF(PrimitiveWithInfer):
def infer_shape(self, uint_crd_f_shape, LJtype_shape, charge_shape, boxlength_f_shape, a_14_shape, b_14_shape,
lj_scale_factor_shape, cf_scale_factor_shape, LJ_type_A_shape, LJ_type_B_shape):
cls_name = self.name
N = self.atom_numbers
M = self.dihedral_14_numbers
Q = LJ_type_A_shape[0]
validator.check_int(uint_crd_f_shape[0], N, Rel.EQ, "uint_crd_f[0]", cls_name)
validator.check_int(uint_crd_f_shape[1], 3, Rel.EQ, "uint_crd_f[1]", cls_name)
validator.check_int(LJtype_shape[0], 3, Rel.EQ, "LJtype", cls_name)
validator.check_int(charge_shape[0], M, Rel.EQ, "charge", cls_name)
validator.check_int(boxlength_f_shape[0], 3, Rel.EQ, "boxlength_f", cls_name)
validator.check_int(a_14_shape[0], M, Rel.EQ, "a_14", cls_name)
validator.check_int(b_14_shape[0], M, Rel.EQ, "b_14", cls_name)
validator.check_int(lj_scale_factor_shape[0], M, Rel.EQ, "lj_scale_factor", cls_name)
validator.check_int(cf_scale_factor_shape[0], M, Rel.EQ, "cf_scale_factor", cls_name)
validator.check_int(LJ_type_B_shape[0], Q, Rel.EQ, "LJ_type_B", cls_name)
return [self.atom_numbers, 3]
def infer_dtype(self, uint_crd_f_dtype, LJtype_dtype, charge_dtype, boxlength_f_type, a_14_type, b_14_type,
@ -1180,7 +1255,9 @@ class Dihedral14LJCFForceWithAtomEnergy(PrimitiveWithInfer):
- **cf_scale_factor** (Tensor, float) - [M,], the scale factor for the
Coulomb part of force correction for each dihedral 1,4 terms.
- **LJ_type_A** (Tensor, float32) - [Q,], the A parameter in Lennard-Jones scheme of each atom pair type.
Q is the number of atom pair.
- **LJ_type_B** (Tensor, float32) - [Q,], the B parameter in Lennard-Jones shceme of each atom pair type.
Q is the number of atom pair.
Outputs:
- **frc_f** (Tensor, float32) - [N, 3], the force felt by each atom.
@ -1192,8 +1269,8 @@ class Dihedral14LJCFForceWithAtomEnergy(PrimitiveWithInfer):
@prim_attr_register
def __init__(self, nb14_numbers, atom_numbers):
assert isinstance(nb14_numbers, int)
assert isinstance(atom_numbers, int)
validator.check_value_type('nb14_numbers', nb14_numbers, (int), self.name)
validator.check_value_type('atom_numbers', atom_numbers, (int), self.name)
self.dihedral_14_numbers = nb14_numbers
self.atom_numbers = atom_numbers
@ -1207,6 +1284,20 @@ class Dihedral14LJCFForceWithAtomEnergy(PrimitiveWithInfer):
def infer_shape(self, uint_crd_f_shape, LJtype_shape, charge_shape, boxlength_f_shape, a_14_shape, b_14_shape,
lj_scale_factor_shape, cf_scale_factor_shape, LJ_type_A_shape, LJ_type_B_shape):
cls_name = self.name
N = self.atom_numbers
M = self.dihedral_14_numbers
Q = LJ_type_A_shape[0]
validator.check_int(uint_crd_f_shape[0], N, Rel.EQ, "uint_crd_f[0]", cls_name)
validator.check_int(uint_crd_f_shape[1], 3, Rel.EQ, "uint_crd_f[1]", cls_name)
validator.check_int(LJtype_shape[0], 3, Rel.EQ, "LJtype", cls_name)
validator.check_int(charge_shape[0], M, Rel.EQ, "charge", cls_name)
validator.check_int(boxlength_f_shape[0], 3, Rel.EQ, "boxlength_f", cls_name)
validator.check_int(a_14_shape[0], M, Rel.EQ, "a_14", cls_name)
validator.check_int(b_14_shape[0], M, Rel.EQ, "b_14", cls_name)
validator.check_int(lj_scale_factor_shape[0], M, Rel.EQ, "lj_scale_factor", cls_name)
validator.check_int(cf_scale_factor_shape[0], M, Rel.EQ, "cf_scale_factor", cls_name)
validator.check_int(LJ_type_B_shape[0], Q, Rel.EQ, "LJ_type_B", cls_name)
return uint_crd_f_shape, charge_shape
def infer_dtype(self, uint_crd_f_dtype, LJtype_dtype, charge_dtype, boxlength_f_type, a_14_type, b_14_type,
@ -1246,7 +1337,9 @@ class Dihedral14LJAtomEnergy(PrimitiveWithInfer):
- **lj_scale_factor** (Tensor, float32) - [M,], the scale factor for the
Lennard-Jones part of force correction of each dihedral 1,4 term.
- **LJ_type_A** (Tensor, float32) - [Q,], the A parameter in Lennard-Jones scheme of each atom pair type.
Q is the number of atom pair.
- **LJ_type_B** (Tensor, float32) - [Q,], the B parameter in Lennard-Jones shceme of each atom pair type.
Q is the number of atom pair.
Outputs:
- **ene** (Tensor, float32) - [N,], the accumulated potential energy of each atom.
@ -1257,8 +1350,8 @@ class Dihedral14LJAtomEnergy(PrimitiveWithInfer):
@prim_attr_register
def __init__(self, nb14_numbers, atom_numbers):
assert isinstance(nb14_numbers, int)
assert isinstance(atom_numbers, int)
validator.check_value_type('nb14_numbers', nb14_numbers, (int), self.name)
validator.check_value_type('atom_numbers', atom_numbers, (int), self.name)
self.dihedral_14_numbers = nb14_numbers
self.atom_numbers = atom_numbers
@ -1271,6 +1364,19 @@ class Dihedral14LJAtomEnergy(PrimitiveWithInfer):
def infer_shape(self, uint_crd_f_shape, LJtype_shape, charge_shape, boxlength_f_shape, a_14_shape, b_14_shape,
lj_scale_factor_shape, LJ_type_A_shape, LJ_type_B_shape):
cls_name = self.name
N = self.atom_numbers
M = self.dihedral_14_numbers
Q = LJ_type_A_shape[0]
validator.check_int(uint_crd_f_shape[0], N, Rel.EQ, "uint_crd_f[0]", cls_name)
validator.check_int(uint_crd_f_shape[1], 3, Rel.EQ, "uint_crd_f[1]", cls_name)
validator.check_int(LJtype_shape[0], 3, Rel.EQ, "LJtype", cls_name)
validator.check_int(charge_shape[0], M, Rel.EQ, "charge", cls_name)
validator.check_int(boxlength_f_shape[0], 3, Rel.EQ, "boxlength_f", cls_name)
validator.check_int(a_14_shape[0], M, Rel.EQ, "a_14", cls_name)
validator.check_int(b_14_shape[0], M, Rel.EQ, "b_14", cls_name)
validator.check_int(lj_scale_factor_shape[0], M, Rel.EQ, "lj_scale_factor", cls_name)
validator.check_int(LJ_type_B_shape[0], Q, Rel.EQ, "LJ_type_B", cls_name)
return LJtype_shape
def infer_dtype(self, uint_crd_f_dtype, LJtype_dtype, charge_dtype, boxlength_f_type, a_14_type, b_14_type,
@ -1297,6 +1403,8 @@ class Dihedral14CFEnergy(PrimitiveWithInfer):
.. math::
dr = (x_a-x_b, y_a-y_b, z_a-z_b)
.. math::
E = k*q_a*q_b/|dr|
Args:
@ -1322,8 +1430,8 @@ class Dihedral14CFEnergy(PrimitiveWithInfer):
@prim_attr_register
def __init__(self, nb14_numbers, atom_numbers):
assert isinstance(nb14_numbers, int)
assert isinstance(atom_numbers, int)
validator.check_value_type('nb14_numbers', nb14_numbers, (int), self.name)
validator.check_value_type('atom_numbers', atom_numbers, (int), self.name)
self.dihedral_14_numbers = nb14_numbers
self.atom_numbers = atom_numbers
@ -1335,6 +1443,17 @@ class Dihedral14CFEnergy(PrimitiveWithInfer):
def infer_shape(self, uint_crd_f_shape, LJtype_shape, charge_shape, boxlength_f_shape, a_14_shape, b_14_shape,
cf_scale_factor_shape):
cls_name = self.name
N = self.atom_numbers
M = self.dihedral_14_numbers
validator.check_int(uint_crd_f_shape[0], N, Rel.EQ, "uint_crd_f[0]", cls_name)
validator.check_int(uint_crd_f_shape[1], 3, Rel.EQ, "uint_crd_f[1]", cls_name)
validator.check_int(LJtype_shape[0], 3, Rel.EQ, "LJtype", cls_name)
validator.check_int(charge_shape[0], M, Rel.EQ, "charge", cls_name)
validator.check_int(boxlength_f_shape[0], 3, Rel.EQ, "boxlength_f", cls_name)
validator.check_int(a_14_shape[0], M, Rel.EQ, "a_14", cls_name)
validator.check_int(b_14_shape[0], M, Rel.EQ, "b_14", cls_name)
validator.check_int(cf_scale_factor_shape[0], M, Rel.EQ, "cf_scale_factor", cls_name)
return [self.dihedral_14_numbers,]
def infer_dtype(self, uint_crd_f_dtype, LJtype_dtype, charge_dtype, boxlength_f_type, a_14_type, b_14_type,
@ -1382,8 +1501,8 @@ class Dihedral14CFAtomEnergy(PrimitiveWithInfer):
@prim_attr_register
def __init__(self, nb14_numbers, atom_numbers):
assert isinstance(nb14_numbers, int)
assert isinstance(atom_numbers, int)
validator.check_value_type('nb14_numbers', nb14_numbers, (int), self.name)
validator.check_value_type('atom_numbers', atom_numbers, (int), self.name)
self.dihedral_14_numbers = nb14_numbers
self.atom_numbers = atom_numbers
@ -1395,6 +1514,17 @@ class Dihedral14CFAtomEnergy(PrimitiveWithInfer):
def infer_shape(self, uint_crd_f_shape, LJtype_shape, charge_shape, boxlength_f_shape, a_14_shape, b_14_shape,
cf_scale_factor_shape):
cls_name = self.name
N = self.atom_numbers
M = self.dihedral_14_numbers
validator.check_int(uint_crd_f_shape[0], N, Rel.EQ, "uint_crd_f[0]", cls_name)
validator.check_int(uint_crd_f_shape[1], 3, Rel.EQ, "uint_crd_f[1]", cls_name)
validator.check_int(LJtype_shape[0], 3, Rel.EQ, "LJtype", cls_name)
validator.check_int(charge_shape[0], M, Rel.EQ, "charge", cls_name)
validator.check_int(boxlength_f_shape[0], 3, Rel.EQ, "boxlength_f", cls_name)
validator.check_int(a_14_shape[0], M, Rel.EQ, "a_14", cls_name)
validator.check_int(b_14_shape[0], M, Rel.EQ, "b_14", cls_name)
validator.check_int(cf_scale_factor_shape[0], M, Rel.EQ, "cf_scale_factor", cls_name)
return LJtype_shape
def infer_dtype(self, uint_crd_f_dtype, LJtype_dtype, charge_dtype, boxlength_f_type, a_14_type, b_14_type,
@ -1450,13 +1580,13 @@ class MDIterationLeapFrog(PrimitiveWithInfer):
@prim_attr_register
def __init__(self, float4_numbers, atom_numbers, half_dt, dt, exp_gamma, is_max_velocity, max_velocity):
assert isinstance(float4_numbers, int)
assert isinstance(atom_numbers, int)
assert isinstance(half_dt, float)
assert isinstance(dt, float)
assert isinstance(exp_gamma, float)
assert isinstance(is_max_velocity, int)
assert isinstance(max_velocity, float)
validator.check_value_type('float4_numbers', float4_numbers, (int), self.name)
validator.check_value_type('atom_numbers', atom_numbers, (int), self.name)
validator.check_value_type('half_dt', half_dt, (float), self.name)
validator.check_value_type('dt', dt, (float), self.name)
validator.check_value_type('exp_gamma', exp_gamma, (float), self.name)
validator.check_value_type('is_max_velocity', is_max_velocity, (int), self.name)
validator.check_value_type('max_velocity', max_velocity, (float), self.name)
self.float4_numbers = float4_numbers
self.atom_numbers = atom_numbers
self.half_dt = half_dt
@ -1477,6 +1607,10 @@ class MDIterationLeapFrog(PrimitiveWithInfer):
self.add_prim_attr('max_velocity', self.max_velocity)
def infer_shape(self, mass_inverse_shape, sqrt_mass_shape):
cls_name = self.name
N = self.atom_numbers
validator.check_int(mass_inverse_shape[0], N, Rel.EQ, "mass_inverse", cls_name)
validator.check_int(sqrt_mass_shape[0], N, Rel.EQ, "sqrt_mass", cls_name)
return [self.atom_numbers, 3], [self.atom_numbers, 3], [self.atom_numbers, 3], [self.atom_numbers, 3]
def infer_dtype(self, mass_inverse_dtype, sqrt_mass_dtype):
@ -1517,11 +1651,11 @@ class PMEReciprocalForce(PrimitiveWithInfer):
@prim_attr_register
def __init__(self, atom_numbers, beta, fftx, ffty, fftz):
assert isinstance(atom_numbers, int)
assert isinstance(beta, float)
assert isinstance(fftx, int)
assert isinstance(ffty, int)
assert isinstance(fftz, int)
validator.check_value_type('atom_numbers', atom_numbers, (int), self.name)
validator.check_value_type('beta', beta, (float), self.name)
validator.check_value_type('fftx', fftx, (int), self.name)
validator.check_value_type('ffty', ffty, (int), self.name)
validator.check_value_type('fftz', fftz, (int), self.name)
self.atom_numbers = atom_numbers
self.beta = beta
self.fftx = fftx
@ -1536,6 +1670,12 @@ class PMEReciprocalForce(PrimitiveWithInfer):
self.add_prim_attr('fftz', self.fftz)
def infer_shape(self, boxlength_shape, uint_crd_shape, charge_shape):
cls_name = self.name
N = self.atom_numbers
validator.check_int(uint_crd_shape[0], N, Rel.EQ, "uint_crd[0]", cls_name)
validator.check_int(uint_crd_shape[1], 3, Rel.EQ, "uint_crd[1]", cls_name)
validator.check_int(boxlength_shape[0], 3, Rel.EQ, "boxlength", cls_name)
validator.check_int(charge_shape[0], N, Rel.EQ, "charge", cls_name)
return uint_crd_shape
def infer_dtype(self, boxlength_type, uint_crd_type, charge_type):
@ -1564,7 +1704,7 @@ class PMEExcludedForce(PrimitiveWithInfer):
- **excluded_list_start** (Tensor, int32) - [N,], the start excluded index
in excluded list for each atom.
- **excluded_list** (Tensor, int32) - [E,], the contiguous join of excluded
list of each atom.
list of each atom. E is the number of excluded atoms.
- **excluded_atom_numbers** (Tensor, int32) - [N,], the number of atom excluded
in excluded list for each atom.
@ -1577,8 +1717,8 @@ class PMEExcludedForce(PrimitiveWithInfer):
@prim_attr_register
def __init__(self, atom_numbers, beta):
assert isinstance(atom_numbers, int)
assert isinstance(beta, float)
validator.check_value_type('atom_numbers', atom_numbers, (int), self.name)
validator.check_value_type('beta', beta, (float), self.name)
self.atom_numbers = atom_numbers
self.beta = beta
self.init_prim_io_names(
@ -1589,6 +1729,14 @@ class PMEExcludedForce(PrimitiveWithInfer):
def infer_shape(self, uint_crd_shape, sacler_shape, charge_shape, excluded_list_start_shape, excluded_list_shape,
excluded_atom_numbers_shape):
cls_name = self.name
N = self.atom_numbers
validator.check_int(uint_crd_shape[0], N, Rel.EQ, "uint_crd[0]", cls_name)
validator.check_int(uint_crd_shape[1], 3, Rel.EQ, "uint_crd[1]", cls_name)
validator.check_int(sacler_shape[0], 3, Rel.EQ, "sacler", cls_name)
validator.check_int(charge_shape[0], N, Rel.EQ, "charge", cls_name)
validator.check_int(excluded_list_start_shape[0], N, Rel.EQ, "excluded_list_start", cls_name)
validator.check_int(excluded_atom_numbers_shape[0], N, Rel.EQ, "excluded_atom_numbers", cls_name)
return uint_crd_shape
def infer_dtype(self, uint_crd_type, sacler_type, charge_type, excluded_list_start_type, excluded_list_type,
@ -1632,7 +1780,7 @@ class PMEEnergy(PrimitiveWithInfer):
- **excluded_list_start** (Tensor, int32) - [N,], the start excluded index
in excluded list for each atom.
- **excluded_list** (Tensor, int32) - [E,], the contiguous join of excluded
list of each atom.
list of each atom. E is the number of excluded atoms.
- **excluded_atom_numbers** (Tensor, int32) - [N,], the number of atom excluded
in excluded list for each atom.
@ -1648,11 +1796,11 @@ class PMEEnergy(PrimitiveWithInfer):
@prim_attr_register
def __init__(self, atom_numbers, beta, fftx, ffty, fftz):
assert isinstance(atom_numbers, int)
assert isinstance(beta, float)
assert isinstance(fftx, int)
assert isinstance(ffty, int)
assert isinstance(fftz, int)
validator.check_value_type('atom_numbers', atom_numbers, (int), self.name)
validator.check_value_type('beta', beta, (float), self.name)
validator.check_value_type('fftx', fftx, (int), self.name)
validator.check_value_type('ffty', ffty, (int), self.name)
validator.check_value_type('fftz', fftz, (int), self.name)
self.atom_numbers = atom_numbers
self.beta = beta
self.fftx = fftx
@ -1670,6 +1818,18 @@ class PMEEnergy(PrimitiveWithInfer):
def infer_shape(self, box_length, uint_crd, charge, nl_numbers, nl_serial, scaler, excluded_list_start,
excluded_list, excluded_atom_numbers):
cls_name = self.name
N = self.atom_numbers
validator.check_int(uint_crd[0], N, Rel.EQ, "uint_crd[0]", cls_name)
validator.check_int(uint_crd[1], 3, Rel.EQ, "uint_crd[1]", cls_name)
validator.check_int(box_length[0], 3, Rel.EQ, "box_length", cls_name)
validator.check_int(charge[0], N, Rel.EQ, "charge", cls_name)
validator.check_int(nl_numbers[0], N, Rel.EQ, "nl_numbers[0]", cls_name)
validator.check_int(nl_serial[0], N, Rel.LE, "nl_serial[0]", cls_name)
validator.check_int(nl_serial[1], 800, Rel.LE, "nl_serial[1]", cls_name)
validator.check_int(excluded_list_start[0], N, Rel.EQ, "excluded_list_start", cls_name)
validator.check_int(excluded_atom_numbers[0], N, Rel.EQ, "excluded_atom_numbers", cls_name)
validator.check_int(excluded_list[0], 0, Rel.GE, "excluded_list", cls_name)
return (1,), (1,), (1,), (1,)
def infer_dtype(self, box_length, uint_crd, charge, nl_numbers, nl_serial, scaler, excluded_list_start,
@ -1701,6 +1861,8 @@ class LJEnergy(PrimitiveWithInfer):
.. math::
dr = (x_a-x_b, y_a-y_b, z_a-z_b)
.. math::
E = A/|dr|^{12} - B/|dr|^{6}
Agrs:
@ -1716,7 +1878,9 @@ class LJEnergy(PrimitiveWithInfer):
- **nl_numbers** - (Tensor, int32) - [N,], the each atom.
- **nl_serial** - (Tensor, int32) - [N, 800], the neighbor list of each atom, the max number is 800.
- **d_LJ_A** (Tensor, float32) - [Q,], the Lennard-Jones A coefficient of each kind of atom pair.
Q is the number of atom pair.
- **d_LJ_B** (Tensor, float32) - [Q,], the Lennard-Jones B coefficient of each kind of atom pair.
Q is the number of atom pair.
Outputs:
- **d_LJ_energy_atom** (Tensor, float32) - [N,], the Lennard-Jones potential energy of each atom.
@ -1728,8 +1892,8 @@ class LJEnergy(PrimitiveWithInfer):
@prim_attr_register
def __init__(self, atom_numbers, cutoff_square):
assert isinstance(atom_numbers, int)
assert isinstance(cutoff_square, float)
validator.check_value_type('atom_numbers', atom_numbers, (int), self.name)
validator.check_value_type('cutoff_square', cutoff_square, (float), self.name)
self.atom_numbers = atom_numbers
self.cutoff_square = cutoff_square
self.init_prim_io_names(
@ -1739,6 +1903,19 @@ class LJEnergy(PrimitiveWithInfer):
self.add_prim_attr('cutoff_square', self.cutoff_square)
def infer_shape(self, uint_crd, LJtype, charge, scaler, nl_numbers, nl_serial, d_LJ_A, d_LJ_B):
cls_name = self.name
N = self.atom_numbers
Q = d_LJ_A[0]
validator.check_int(uint_crd[0], N, Rel.EQ, "uint_crd[0]", cls_name)
validator.check_int(uint_crd[1], 3, Rel.EQ, "uint_crd[1]", cls_name)
validator.check_int(LJtype[0], N, Rel.EQ, "LJtype", cls_name)
validator.check_int(charge[0], 3, Rel.EQ, "charge", cls_name)
validator.check_int(scaler[0], 3, Rel.EQ, "scaler", cls_name)
validator.check_int(nl_numbers[0], N, Rel.EQ, "nl_numbers", cls_name)
validator.check_int(nl_serial[0], N, Rel.EQ, "nl_serial[0]", cls_name)
validator.check_int(nl_serial[1], 800, Rel.LE, "nl_serial[1]", cls_name)
validator.check_int(scaler[0], 3, Rel.EQ, "scaler", cls_name)
validator.check_int(d_LJ_B[0], Q, Rel.EQ, "d_LJ_B[0]", cls_name)
return charge
def infer_dtype(self, uint_crd, LJtype, charge, scaler, nl_numbers, nl_serial, d_LJ_A, d_LJ_B):
@ -1761,6 +1938,9 @@ class LJForce(PrimitiveWithInfer):
.. math::
dr = (x_a-x_b, y_a-y_b, z_a-z_b)
.. math::
F = (-12*A/|dr|^{14} + 6*B/|dr|^{8}) * dr
Agrs:
@ -1776,7 +1956,9 @@ class LJForce(PrimitiveWithInfer):
- **nl_numbers** - (Tensor, int32) - [N,], the each atom.
- **nl_serial** - (Tensor, int32) - [N, 800], the neighbor list of each atom, the max number is 800.
- **d_LJ_A** (Tensor, float32) - [Q,], the Lennard-Jones A coefficient of each kind of atom pair.
Q is the number of atom pair.
- **d_LJ_B** (Tensor, float32) - [Q,], the Lennard-Jones B coefficient of each kind of atom pair.
Q is the number of atom pair.
outputs:
- **frc** (Tensor, float32) - [N, 3], the force felt by each atom.
@ -1787,8 +1969,8 @@ class LJForce(PrimitiveWithInfer):
@prim_attr_register
def __init__(self, atom_numbers, cutoff_square):
assert isinstance(atom_numbers, int)
assert isinstance(cutoff_square, float)
validator.check_value_type('atom_numbers', atom_numbers, (int), self.name)
validator.check_value_type('cutoff_square', cutoff_square, (float), self.name)
self.atom_numbers = atom_numbers
self.cutoff_square = cutoff_square
self.init_prim_io_names(
@ -1798,6 +1980,19 @@ class LJForce(PrimitiveWithInfer):
self.add_prim_attr('cutoff_square', self.cutoff_square)
def infer_shape(self, uint_crd, LJtype, charge, scaler, nl_numbers, nl_serial, d_LJ_A, d_LJ_B):
cls_name = self.name
N = self.atom_numbers
Q = d_LJ_A[0]
validator.check_int(uint_crd[0], N, Rel.EQ, "uint_crd[0]", cls_name)
validator.check_int(uint_crd[1], 3, Rel.EQ, "uint_crd[1]", cls_name)
validator.check_int(LJtype[0], N, Rel.EQ, "LJtype", cls_name)
validator.check_int(charge[0], 3, Rel.EQ, "charge", cls_name)
validator.check_int(scaler[0], 3, Rel.EQ, "scaler", cls_name)
validator.check_int(nl_numbers[0], N, Rel.EQ, "nl_numbers", cls_name)
validator.check_int(nl_serial[0], N, Rel.EQ, "nl_serial[0]", cls_name)
validator.check_int(nl_serial[1], 800, Rel.LE, "nl_serial[1]", cls_name)
validator.check_int(scaler[0], 3, Rel.EQ, "scaler", cls_name)
validator.check_int(d_LJ_B[0], Q, Rel.EQ, "d_LJ_B[0]", cls_name)
return uint_crd
def infer_dtype(self, uint_crd, LJtype, charge, scaler, nl_numbers, nl_serial, d_LJ_A, d_LJ_B):
@ -1833,7 +2028,9 @@ class LJForceWithPMEDirectForce(PrimitiveWithInfer):
- **nl_numbers** - (Tensor, int32) - [N,], the each atom.
- **nl_serial** - (Tensor, int32) - [N, 800], the neighbor list of each atom, the max number is 800.
- **d_LJ_A** (Tensor, float32) - [Q,], the Lennard-Jones A coefficient of each kind of atom pair.
Q is the number of atom pair.
- **d_LJ_B** (Tensor, float32) - [Q,], the Lennard-Jones B coefficient of each kind of atom pair.
Q is the number of atom pair.
Outputs:
- **frc** (Tensor, float32), [N, 3], the force felt by each atom.
@ -1844,9 +2041,9 @@ class LJForceWithPMEDirectForce(PrimitiveWithInfer):
@prim_attr_register
def __init__(self, atom_numbers, cutoff, pme_beta):
assert isinstance(atom_numbers, int)
assert isinstance(cutoff, float)
assert isinstance(pme_beta, float)
validator.check_value_type('atom_numbers', atom_numbers, (int), self.name)
validator.check_value_type('cutoff', cutoff, (float), self.name)
validator.check_value_type('pme_beta', pme_beta, (float), self.name)
self.atom_numbers = atom_numbers
self.cutoff = cutoff
self.pme_beta = pme_beta
@ -1858,6 +2055,19 @@ class LJForceWithPMEDirectForce(PrimitiveWithInfer):
self.add_prim_attr('pme_beta', self.pme_beta)
def infer_shape(self, uint_crd, LJtype, charge, scaler, nl_numbers, nl_serial, d_LJ_A, d_LJ_B):
cls_name = self.name
N = self.atom_numbers
Q = d_LJ_A[0]
validator.check_int(uint_crd[0], N, Rel.EQ, "uint_crd[0]", cls_name)
validator.check_int(uint_crd[1], 3, Rel.EQ, "uint_crd[1]", cls_name)
validator.check_int(LJtype[0], N, Rel.EQ, "LJtype", cls_name)
validator.check_int(charge[0], 3, Rel.EQ, "charge", cls_name)
validator.check_int(scaler[0], 3, Rel.EQ, "scaler", cls_name)
validator.check_int(nl_numbers[0], N, Rel.EQ, "nl_numbers", cls_name)
validator.check_int(nl_serial[0], N, Rel.EQ, "nl_serial[0]", cls_name)
validator.check_int(nl_serial[1], 800, Rel.LE, "nl_serial[1]", cls_name)
validator.check_int(scaler[0], 3, Rel.EQ, "scaler", cls_name)
validator.check_int(d_LJ_B[0], Q, Rel.EQ, "d_LJ_B[0]", cls_name)
return uint_crd
def infer_dtype(self, uint_crd, LJtype, charge, scaler, nl_numbers, nl_serial, d_LJ_A, d_LJ_B):
@ -1882,6 +2092,8 @@ class GetCenterOfGeometry(PrimitiveWithInfer):
@prim_attr_register
def __init__(self, center_numbers, center_numbers_inverse):
validator.check_value_type('center_numbers', center_numbers, (int), self.name)
validator.check_value_type('center_numbers_inverse', center_numbers_inverse, (float), self.name)
self.center_numbers = center_numbers
self.center_numbers_inverse = center_numbers_inverse
self.add_prim_attr('center_numbers', self.center_numbers)
@ -1894,8 +2106,8 @@ class GetCenterOfGeometry(PrimitiveWithInfer):
cls_name = self.name
N = self.center_numbers
validator.check_int(center_atoms_shape[0], N, Rel.EQ, "center_atoms", cls_name)
validator.check_int(crd_f_shape[0], N, Rel.EQ, "crd_f", cls_name)
validator.check_int(crd_f_shape[1], 3, Rel.EQ, "crd_f", cls_name)
validator.check_int(crd_f_shape[0], N, Rel.EQ, "crd_f[0]", cls_name)
validator.check_int(crd_f_shape[1], 3, Rel.EQ, "crd_f[1]", cls_name)
return [3,]
def infer_dtype(self, center_atoms_dtype, crd_f_dtype):
@ -1990,6 +2202,7 @@ class NeighborListUpdate(PrimitiveWithInfer):
between the unsigned int value and the real space coordinates.
- **uint_crd** (Tensor, uint32) - [N, 3], the unsigned int coordinates value fo each atom.
- **gpointer** (Tensor, int32) - [G, 125], the 125 nearest neighbor grids (including self) of each grid.
G is the number of nearest neighbor grids.
- **nl_atom_numbers** (Tensor, int32) - [N,], the number of atoms in neighbor list of each atom.
- **nl_atom_serial** (Tensor, int32) - [N, L], the indices of atoms in neighbor list of each atom.
- **uint_dr_to_dr_cof** (Tensor, float32) - [3,], the scale factor between
@ -2182,13 +2395,13 @@ class MDIterationLeapFrogWithRF(PrimitiveWithInfer):
@prim_attr_register
def __init__(self, float4_numbers, atom_numbers, half_dt, dt, exp_gamma, is_max_velocity, max_velocity):
assert isinstance(float4_numbers, int)
assert isinstance(atom_numbers, int)
assert isinstance(half_dt, float)
assert isinstance(dt, float)
assert isinstance(exp_gamma, float)
assert isinstance(is_max_velocity, int)
assert isinstance(max_velocity, float)
validator.check_value_type('float4_numbers', float4_numbers, (int), self.name)
validator.check_value_type('atom_numbers', atom_numbers, (int), self.name)
validator.check_value_type('half_dt', half_dt, (float), self.name)
validator.check_value_type('dt', dt, (float), self.name)
validator.check_value_type('exp_gamma', exp_gamma, (float), self.name)
validator.check_value_type('is_max_velocity', is_max_velocity, (int), self.name)
validator.check_value_type('max_velocity', max_velocity, (float), self.name)
self.float4_numbers = float4_numbers
self.atom_numbers = atom_numbers
self.half_dt = half_dt

0
model_zoo/research/hpc/sponge/src/__init__.py Normal file
View File

2
model_zoo/research/hpc/sponge/src/nb14.py
View File

@ -82,7 +82,7 @@ class NON_BOND_14(nn.Cell):
self.cf_scale_type = [0] * self.dihedral_type_numbers
self.lj_scale_type = [0] * self.dihedral_type_numbers
self.process1(context)
self.h_atom_a = [0] * self.dihedral_numbers
self.h_atom_b = [0] * self.dihedral_numbers
self.h_lj_scale_factor = [0] * self.dihedral_numbers

22
model_zoo/research/hpc/sponge/src/simulation_initial.py
View File

@ -18,15 +18,15 @@ import numpy as np
import mindspore.common.dtype as mstype
from mindspore import Tensor, nn
from Langevin_Liujian_md import Langevin_Liujian
from angle import Angle
from bond import Bond
from dihedral import Dihedral
from lennard_jones import Lennard_Jones_Information
from md_information import md_information
from nb14 import NON_BOND_14
from neighbor_list import nb_infomation
from particle_mesh_ewald import Particle_Mesh_Ewald
from .Langevin_Liujian_md import Langevin_Liujian
from .angle import Angle
from .bond import Bond
from .dihedral import Dihedral
from .lennard_jones import Lennard_Jones_Information
from .md_information import md_information
from .nb14 import NON_BOND_14
from .neighbor_list import nb_infomation
from .particle_mesh_ewald import Particle_Mesh_Ewald
class controller:
@ -102,7 +102,8 @@ class Simulation(nn.Cell):
nb_info = self.nb_info
pme_method = self.pme_method
bond_frc, _ = self.bond.Bond_Force_With_Atom_Energy(md_info.uint_crd, md_info.uint_dr_to_dr_cof)
frc_t = bond_frc.asnumpy()
frc_t = 0
frc_t += bond_frc.asnumpy()
angle_frc, _ = self.angle.Angle_Force_With_Atom_Energy(md_info.uint_crd, md_info.uint_dr_to_dr_cof)
frc_t += angle_frc.asnumpy()
@ -180,6 +181,7 @@ class Simulation(nn.Cell):
if md_info.mode > 0 and int(control.Command_Set["thermostat"]) == 1:
md_info.vel, md_info.crd, md_info.frc, md_info.acc = liujian_info.MD_Iteration_Leap_Frog(
md_info.d_mass_inverse, md_info.vel, md_info.crd, md_info.frc)
self.Main_After_Iteration()
def Main_After_Iteration(self):
"""main after iteration"""